FlagEmbedding/Tutorials/1_Embedding/1.2.1_BGE_Series.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "06cff9e4",
   "metadata": {},
   "source": [
    "# BGE Series"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "880e229d",
   "metadata": {},
   "source": [
    "In this Part, we will walk through the BGE series and introduce how to use the BGE embedding models."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2516fd49",
   "metadata": {},
   "source": [
    "## 1. BAAI General Embedding"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2113ee71",
   "metadata": {},
   "source": [
    "BGE stands for BAAI General Embedding, it's a series of embeddings models developed and published by Beijing Academy of Artificial Intelligence (BAAI)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16515b99",
   "metadata": {},
   "source": [
    "A full support of APIs and related usages of BGE is maintained in [FlagEmbedding](https://github.com/FlagOpen/FlagEmbedding) on GitHub.\n",
    "\n",
    "Run the following cell to install FlagEmbedding in your environment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88095fd0",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "%pip install -U FlagEmbedding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a2376217",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os \n",
    "os.environ['TRANSFORMERS_NO_ADVISORY_WARNINGS'] = 'true'\n",
    "# single GPU is better for small tasks\n",
    "os.environ['CUDA_VISIBLE_DEVICES'] = '0'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc6e30a0",
   "metadata": {},
   "source": [
    "The collection of BGE models can be found in [Huggingface collection](https://huggingface.co/collections/BAAI/bge-66797a74476eb1f085c7446d)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67a16ccf",
   "metadata": {},
   "source": [
    "## 2. BGE Series Models"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e10034a",
   "metadata": {},
   "source": [
    "### 2.1 BGE"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0cdc6702",
   "metadata": {},
   "source": [
    "The very first version of BGE has 6 models, with 'large', 'base', and 'small' for English and Chinese. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04b75f72",
   "metadata": {},
   "source": [
    "| Model  | Language |   Parameters   |   Model Size   |    Description    |   Base Model     |\n",
    "|:-------|:--------:|:--------------:|:--------------:|:-----------------:|:----------------:|\n",
    "| [BAAI/bge-large-en](https://huggingface.co/BAAI/bge-large-en)   | English |    500M    |    1.34 GB   |              Embedding Model which map text into vector                            |  BERT  |\n",
    "| [BAAI/bge-base-en](https://huggingface.co/BAAI/bge-base-en)     | English |    109M    |    438 MB    |          a base-scale model but with similar ability to `bge-large-en`  |  BERT  |\n",
    "| [BAAI/bge-small-en](https://huggingface.co/BAAI/bge-small-en)   | English |    33.4M   |    133 MB    |          a small-scale model but with competitive performance                    |  BERT  |\n",
    "| [BAAI/bge-large-zh](https://huggingface.co/BAAI/bge-large-zh)   | Chinese |    326M    |    1.3 GB    |              Embedding Model which map text into vector                            |  BERT  |\n",
    "| [BAAI/bge-base-zh](https://huggingface.co/BAAI/bge-base-zh)     | Chinese |    102M    |    409 MB    |           a base-scale model but with similar ability to `bge-large-zh`           |  BERT  |\n",
    "| [BAAI/bge-small-zh](https://huggingface.co/BAAI/bge-small-zh)   | Chinese |    24M     |    95.8 MB   |           a small-scale model but with competitive performance                    |  BERT  |"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9c45d17",
   "metadata": {},
   "source": [
    "For inference, simply import FlagModel from FlagEmbedding and initialize the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "89e07751",
   "metadata": {},
   "outputs": [],
   "source": [
    "from FlagEmbedding import FlagModel\n",
    "\n",
    "# Load BGE model\n",
    "model = FlagModel(\n",
    "    'BAAI/bge-base-en',\n",
    "    query_instruction_for_retrieval=\"Represent this sentence for searching relevant passages:\",\n",
    "    query_instruction_format='{}{}'\n",
    ")\n",
    "\n",
    "queries = [\"query 1\", \"query 2\"]\n",
    "corpus = [\"passage 1\", \"passage 2\"]\n",
    "\n",
    "# encode the queries and corpus\n",
    "q_embeddings = model.encode_queries(queries)\n",
    "p_embeddings = model.encode_corpus(corpus)\n",
    "\n",
    "# compute the similarity scores\n",
    "scores = q_embeddings @ p_embeddings.T\n",
    "print(scores)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c8e69ed",
   "metadata": {},
   "source": [
    "For general encoding, use either `encode()`:\n",
    "```python\n",
    "FlagModel.encode(sentences, batch_size=256, max_length=512, convert_to_numpy=True)\n",
    "```\n",
    "or `encode_corpus()` that directly calls `encode()`:\n",
    "```python\n",
    "FlagModel.encode_corpus(corpus, batch_size=256, max_length=512, convert_to_numpy=True)\n",
    "```\n",
    "The *encode_queries()* function concatenate the `query_instruction_for_retrieval` with each of the input query to form the new sentences and then feed them to `encode()`.\n",
    "```python\n",
    "FlagModel.encode_queries(queries, batch_size=256, max_length=512, convert_to_numpy=True)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c86a5a3",
   "metadata": {},
   "source": [
    "### 2.2 BGE v1.5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "454ff7aa",
   "metadata": {},
   "source": [
    "BGE 1.5 alleviate the issue of the similarity distribution, and enhance retrieval ability without instruction."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30b1f897",
   "metadata": {},
   "source": [
    "| Model  | Language |   Parameters   |   Model Size   |    Description    |   Base Model     |\n",
    "|:-------|:--------:|:--------------:|:--------------:|:-----------------:|:----------------:|\n",
    "| [BAAI/bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5)   | English |    335M    |    1.34 GB   |     version 1.5 with more reasonable similarity distribution      |   BERT   |\n",
    "| [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5)     | English |    109M    |    438 MB    |     version 1.5 with more reasonable similarity distribution      |   BERT   |\n",
    "| [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5)   | English |    33.4M   |    133 MB    |     version 1.5 with more reasonable similarity distribution      |   BERT   |\n",
    "| [BAAI/bge-large-zh-v1.5](https://huggingface.co/BAAI/bge-large-zh-v1.5)   | Chinese |    326M    |    1.3 GB    |     version 1.5 with more reasonable similarity distribution      |   BERT   |\n",
    "| [BAAI/bge-base-zh-v1.5](https://huggingface.co/BAAI/bge-base-zh-v1.5)     | Chinese |    102M    |    409 MB    |     version 1.5 with more reasonable similarity distribution      |   BERT   |\n",
    "| [BAAI/bge-small-zh-v1.5](https://huggingface.co/BAAI/bge-small-zh-v1.5)   | Chinese |    24M     |    95.8 MB   |     version 1.5 with more reasonable similarity distribution      |   BERT   |"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed00c504",
   "metadata": {},
   "source": [
    "You can use BGE 1.5 models exactly same to BGE v1 models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9b17afcc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.736794  0.5989914]\n",
      " [0.5684842 0.7461165]]\n"
     ]
    }
   ],
   "source": [
    "model = FlagModel(\n",
    "    'BAAI/bge-base-en-v1.5',\n",
    "    query_instruction_for_retrieval=\"Represent this sentence for searching relevant passages:\",\n",
    "    query_instruction_format='{}{}'\n",
    ")\n",
    "\n",
    "queries = [\"query 1\", \"query 2\"]\n",
    "corpus = [\"passage 1\", \"passage 2\"]\n",
    "\n",
    "# encode the queries and corpus\n",
    "q_embeddings = model.encode_queries(queries)\n",
    "p_embeddings = model.encode_corpus(corpus)\n",
    "\n",
    "# compute the similarity scores\n",
    "scores = q_embeddings @ p_embeddings.T\n",
    "print(scores)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcf2a82b",
   "metadata": {},
   "source": [
    "### 2.3 BGE M3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc5b5a5e",
   "metadata": {},
   "source": [
    "BGE-M3 is the new version of BGE models that is distinguished for its versatility in:\n",
    "- Multi-Functionality: Simultaneously perform the three common retrieval functionalities of embedding model: dense retrieval, multi-vector retrieval, and sparse retrieval.\n",
    "- Multi-Linguality: Supports more than 100 working languages.\n",
    "- Multi-Granularity: Can proces inputs with different granularityies, spanning from short sentences to long documents of up to 8192 tokens.\n",
    "\n",
    "For more details, feel free to check out the [paper](https://arxiv.org/pdf/2402.03216)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41348e03",
   "metadata": {},
   "source": [
    "| Model  | Language |   Parameters   |   Model Size   |    Description    |   Base Model     |\n",
    "|:-------|:--------:|:--------------:|:--------------:|:-----------------:|:----------------:|\n",
    "| [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3)                   |    Multilingual     |   568M   |  2.27 GB  |  Multi-Functionality(dense retrieval, sparse retrieval, multi-vector(colbert)), Multi-Linguality, and Multi-Granularity(8192 tokens) | XLM-RoBERTa |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d4647625",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fetching 30 files: 100%|██████████| 30/30 [00:00<00:00, 228780.22it/s]\n"
     ]
    }
   ],
   "source": [
    "from FlagEmbedding import BGEM3FlagModel\n",
    "\n",
    "model = BGEM3FlagModel('BAAI/bge-m3', use_fp16=True)\n",
    "\n",
    "sentences = [\"What is BGE M3?\", \"Defination of BM25\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f89f1a9",
   "metadata": {},
   "source": [
    "```python\n",
    "BGEM3FlagModel.encode(\n",
    "    sentences, \n",
    "    batch_size=12, \n",
    "    max_length=8192, \n",
    "    return_dense=True, \n",
    "    return_sparse=False, \n",
    "    return_colbert_vecs=False\n",
    ")\n",
    "```\n",
    "It returns a dictionary like:\n",
    "```python\n",
    "{\n",
    "    'dense_vecs':       # array of dense embeddings of inputs if return_dense=True, otherwise None,\n",
    "    'lexical_weights':  # array of dictionaries with keys and values are ids of tokens and their corresponding weights if return_sparse=True, otherwise None,\n",
    "    'colbert_vecs':     # array of multi-vector embeddings of inputs if return_cobert_vecs=True, otherwise None,'\n",
    "}\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f0b11cf0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# If you don't need such a long length of 8192 input tokens, you can set max_length to a smaller value to speed up encoding.\n",
    "embeddings = model.encode(\n",
    "    sentences, \n",
    "    max_length=10,\n",
    "    return_dense=True, \n",
    "    return_sparse=True, \n",
    "    return_colbert_vecs=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "72cba126",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dense embedding:\n",
      "[[-0.03411707 -0.04707828 -0.00089447 ...  0.04828531  0.00755427\n",
      "  -0.02961654]\n",
      " [-0.01041734 -0.04479263 -0.02429199 ... -0.00819298  0.01503995\n",
      "   0.01113793]]\n",
      "sparse embedding:\n",
      "[defaultdict(<class 'int'>, {'4865': 0.08362077, '83': 0.081469566, '335': 0.12964639, '11679': 0.25186998, '276': 0.17001738, '363': 0.26957875, '32': 0.040755156}), defaultdict(<class 'int'>, {'262': 0.050144322, '5983': 0.13689369, '2320': 0.045134712, '111': 0.06342201, '90017': 0.25167602, '2588': 0.33353207})]\n",
      "multi-vector:\n",
      "[array([[-8.6726490e-03, -4.8921868e-02, -3.0449261e-03, ...,\n",
      "        -2.2082448e-02,  5.7268854e-02,  1.2811369e-02],\n",
      "       [-8.8765034e-03, -4.6860173e-02, -9.5845405e-03, ...,\n",
      "        -3.1404708e-02,  5.3911421e-02,  6.8714428e-03],\n",
      "       [ 1.8445771e-02, -4.2359587e-02,  8.6754939e-04, ...,\n",
      "        -1.9803897e-02,  3.8384371e-02,  7.6852231e-03],\n",
      "       ...,\n",
      "       [-2.5543230e-02, -1.6561864e-02, -4.2125367e-02, ...,\n",
      "        -4.5030322e-02,  4.4091221e-02, -1.0043185e-02],\n",
      "       [ 4.9905590e-05, -5.5475257e-02,  8.4884483e-03, ...,\n",
      "        -2.2911752e-02,  6.0379632e-02,  9.3577225e-03],\n",
      "       [ 2.5895271e-03, -2.9331330e-02, -1.8961012e-02, ...,\n",
      "        -8.0389353e-03,  3.2842189e-02,  4.3894034e-02]], dtype=float32), array([[ 0.01715658,  0.03835309, -0.02311821, ...,  0.00146474,\n",
      "         0.02993429, -0.05985384],\n",
      "       [ 0.00996143,  0.039217  , -0.03855301, ...,  0.00599566,\n",
      "         0.02722942, -0.06509776],\n",
      "       [ 0.01777726,  0.03919311, -0.01709837, ...,  0.00805702,\n",
      "         0.03988946, -0.05069073],\n",
      "       ...,\n",
      "       [ 0.05474931,  0.0075684 ,  0.00329455, ..., -0.01651684,\n",
      "         0.02397249,  0.00368039],\n",
      "       [ 0.0093503 ,  0.05022853, -0.02385841, ...,  0.02575599,\n",
      "         0.00786822, -0.03260205],\n",
      "       [ 0.01805054,  0.01337725,  0.00016697, ...,  0.01843987,\n",
      "         0.01374448,  0.00310114]], dtype=float32)]\n"
     ]
    }
   ],
   "source": [
    "print(f\"dense embedding:\\n{embeddings['dense_vecs']}\")\n",
    "print(f\"sparse embedding:\\n{embeddings['lexical_weights']}\")\n",
    "print(f\"multi-vector:\\n{embeddings['colbert_vecs']}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14d83caa",
   "metadata": {},
   "source": [
    "### 2.4 BGE Multilingual Gemma2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8ec545bc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8b7b2aa4",
   "metadata": {},
   "source": [
    "### 2.4 BGE ICL"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c9acb92",
   "metadata": {},
   "source": [
    "BGE ICL stands for in-context learning. By providing few-shot examples in the query, it can significantly enhance the model's ability to handle new tasks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4595bae7",
   "metadata": {},
   "outputs": [],
   "source": [
    "documents = [\n",
    "    \"As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.\",\n",
    "    \"Definition of summit for English Language Learners. : 1  the highest point of a mountain : the top of a mountain. : 2  the highest level. : 3  a meeting or series of meetings between the leaders of two or more governments.\"\n",
    "]\n",
    "\n",
    "examples = [\n",
    "    {\n",
    "        'instruct': 'Given a web search query, retrieve relevant passages that answer the query.',\n",
    "        'query': 'what is a virtual interface',\n",
    "        'response': \"A virtual interface is a software-defined abstraction that mimics the behavior and characteristics of a physical network interface. It allows multiple logical network connections to share the same physical network interface, enabling efficient utilization of network resources. Virtual interfaces are commonly used in virtualization technologies such as virtual machines and containers to provide network connectivity without requiring dedicated hardware. They facilitate flexible network configurations and help in isolating network traffic for security and management purposes.\"\n",
    "    },\n",
    "    {\n",
    "        'instruct': 'Given a web search query, retrieve relevant passages that answer the query.',\n",
    "        'query': 'causes of back pain in female for a week',\n",
    "        'response': \"Back pain in females lasting a week can stem from various factors. Common causes include muscle strain due to lifting heavy objects or improper posture, spinal issues like herniated discs or osteoporosis, menstrual cramps causing referred pain, urinary tract infections, or pelvic inflammatory disease. Pregnancy-related changes can also contribute. Stress and lack of physical activity may exacerbate symptoms. Proper diagnosis by a healthcare professional is crucial for effective treatment and management.\"\n",
    "    }\n",
    "]\n",
    "\n",
    "queries = [\"how much protein should a female eat\", \"summit define\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ffb586c6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading shards:   0%|          | 0/3 [00:10<?, ?it/s]\n"
     ]
    },
    {
     "ename": "OSError",
     "evalue": "We couldn't connect to 'https://huggingface.co' to load this file, couldn't find it in the cached files and it looks like BAAI/bge-en-icl is not the path to a directory containing a file named model-00001-of-00003.safetensors.\nCheckout your internet connection or see how to run the library in offline mode at 'https://huggingface.co/docs/transformers/installation#offline-mode'.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTimeoutError\u001b[0m                              Traceback (most recent call last)",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/urllib3/connection.py:199\u001b[0m, in \u001b[0;36mHTTPConnection._new_conn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    198\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 199\u001b[0m     sock \u001b[38;5;241m=\u001b[39m \u001b[43mconnection\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate_connection\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    200\u001b[0m \u001b[43m        \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_dns_host\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mport\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    201\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    202\u001b[0m \u001b[43m        \u001b[49m\u001b[43msource_address\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msource_address\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    203\u001b[0m \u001b[43m        \u001b[49m\u001b[43msocket_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msocket_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    204\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    205\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m socket\u001b[38;5;241m.\u001b[39mgaierror \u001b[38;5;28;01mas\u001b[39;00m e:\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/urllib3/util/connection.py:85\u001b[0m, in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[1;32m     84\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 85\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m err\n\u001b[1;32m     86\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m     87\u001b[0m     \u001b[38;5;66;03m# Break explicitly a reference cycle\u001b[39;00m\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/urllib3/util/connection.py:73\u001b[0m, in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[1;32m     72\u001b[0m     sock\u001b[38;5;241m.\u001b[39mbind(source_address)\n\u001b[0;32m---> 73\u001b[0m \u001b[43msock\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[43msa\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     74\u001b[0m \u001b[38;5;66;03m# Break explicitly a reference cycle\u001b[39;00m\n",
      "\u001b[0;31mTimeoutError\u001b[0m: timed out",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mConnectTimeoutError\u001b[0m                       Traceback (most recent call last)",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/urllib3/connectionpool.py:789\u001b[0m, in \u001b[0;36mHTTPConnectionPool.urlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)\u001b[0m\n\u001b[1;32m    788\u001b[0m \u001b[38;5;66;03m# Make the request on the HTTPConnection object\u001b[39;00m\n\u001b[0;32m--> 789\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    790\u001b[0m \u001b[43m    \u001b[49m\u001b[43mconn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    791\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    792\u001b[0m \u001b[43m    \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    793\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout_obj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    794\u001b[0m \u001b[43m    \u001b[49m\u001b[43mbody\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbody\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    795\u001b[0m \u001b[43m    \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    796\u001b[0m \u001b[43m    \u001b[49m\u001b[43mchunked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunked\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    797\u001b[0m \u001b[43m    \u001b[49m\u001b[43mretries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mretries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    798\u001b[0m \u001b[43m    \u001b[49m\u001b[43mresponse_conn\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mresponse_conn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    799\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpreload_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpreload_content\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    800\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdecode_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdecode_content\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    801\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mresponse_kw\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    802\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    804\u001b[0m \u001b[38;5;66;03m# Everything went great!\u001b[39;00m\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/urllib3/connectionpool.py:490\u001b[0m, in \u001b[0;36mHTTPConnectionPool._make_request\u001b[0;34m(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)\u001b[0m\n\u001b[1;32m    489\u001b[0m         new_e \u001b[38;5;241m=\u001b[39m _wrap_proxy_error(new_e, conn\u001b[38;5;241m.\u001b[39mproxy\u001b[38;5;241m.\u001b[39mscheme)\n\u001b[0;32m--> 490\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m new_e\n\u001b[1;32m    492\u001b[0m \u001b[38;5;66;03m# conn.request() calls http.client.*.request, not the method in\u001b[39;00m\n\u001b[1;32m    493\u001b[0m \u001b[38;5;66;03m# urllib3.request. It also calls makefile (recv) on the socket.\u001b[39;00m\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/urllib3/connectionpool.py:466\u001b[0m, in \u001b[0;36mHTTPConnectionPool._make_request\u001b[0;34m(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)\u001b[0m\n\u001b[1;32m    465\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 466\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_validate_conn\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconn\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    467\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (SocketTimeout, BaseSSLError) \u001b[38;5;28;01mas\u001b[39;00m e:\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/urllib3/connectionpool.py:1095\u001b[0m, in \u001b[0;36mHTTPSConnectionPool._validate_conn\u001b[0;34m(self, conn)\u001b[0m\n\u001b[1;32m   1094\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m conn\u001b[38;5;241m.\u001b[39mis_closed:\n\u001b[0;32m-> 1095\u001b[0m     \u001b[43mconn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1097\u001b[0m \u001b[38;5;66;03m# TODO revise this, see https://github.com/urllib3/urllib3/issues/2791\u001b[39;00m\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/urllib3/connection.py:693\u001b[0m, in \u001b[0;36mHTTPSConnection.connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    692\u001b[0m sock: socket\u001b[38;5;241m.\u001b[39msocket \u001b[38;5;241m|\u001b[39m ssl\u001b[38;5;241m.\u001b[39mSSLSocket\n\u001b[0;32m--> 693\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msock \u001b[38;5;241m=\u001b[39m sock \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_new_conn\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    694\u001b[0m server_hostname: \u001b[38;5;28mstr\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhost\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/urllib3/connection.py:208\u001b[0m, in \u001b[0;36mHTTPConnection._new_conn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    207\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m SocketTimeout \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m--> 208\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m ConnectTimeoutError(\n\u001b[1;32m    209\u001b[0m         \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m    210\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mConnection to \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhost\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m timed out. (connect timeout=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtimeout\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m)\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m    211\u001b[0m     ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n\u001b[1;32m    213\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
      "\u001b[0;31mConnectTimeoutError\u001b[0m: (<urllib3.connection.HTTPSConnection object at 0x7fcefad9e2a0>, 'Connection to huggingface.co timed out. (connect timeout=10)')",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mMaxRetryError\u001b[0m                             Traceback (most recent call last)",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/requests/adapters.py:667\u001b[0m, in \u001b[0;36mHTTPAdapter.send\u001b[0;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[1;32m    666\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 667\u001b[0m     resp \u001b[38;5;241m=\u001b[39m \u001b[43mconn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43murlopen\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    668\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    669\u001b[0m \u001b[43m        \u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    670\u001b[0m \u001b[43m        \u001b[49m\u001b[43mbody\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbody\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    671\u001b[0m \u001b[43m        \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    672\u001b[0m \u001b[43m        \u001b[49m\u001b[43mredirect\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    673\u001b[0m \u001b[43m        \u001b[49m\u001b[43massert_same_host\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    674\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpreload_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    675\u001b[0m \u001b[43m        \u001b[49m\u001b[43mdecode_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    676\u001b[0m \u001b[43m        \u001b[49m\u001b[43mretries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmax_retries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    677\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    678\u001b[0m \u001b[43m        \u001b[49m\u001b[43mchunked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunked\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    679\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    681\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (ProtocolError, \u001b[38;5;167;01mOSError\u001b[39;00m) \u001b[38;5;28;01mas\u001b[39;00m err:\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/urllib3/connectionpool.py:843\u001b[0m, in \u001b[0;36mHTTPConnectionPool.urlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)\u001b[0m\n\u001b[1;32m    841\u001b[0m     new_e \u001b[38;5;241m=\u001b[39m ProtocolError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mConnection aborted.\u001b[39m\u001b[38;5;124m\"\u001b[39m, new_e)\n\u001b[0;32m--> 843\u001b[0m retries \u001b[38;5;241m=\u001b[39m \u001b[43mretries\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mincrement\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    844\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merror\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnew_e\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m_pool\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m_stacktrace\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msys\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexc_info\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[1;32m    845\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    846\u001b[0m retries\u001b[38;5;241m.\u001b[39msleep()\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/urllib3/util/retry.py:519\u001b[0m, in \u001b[0;36mRetry.increment\u001b[0;34m(self, method, url, response, error, _pool, _stacktrace)\u001b[0m\n\u001b[1;32m    518\u001b[0m     reason \u001b[38;5;241m=\u001b[39m error \u001b[38;5;129;01mor\u001b[39;00m ResponseError(cause)\n\u001b[0;32m--> 519\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m MaxRetryError(_pool, url, reason) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mreason\u001b[39;00m  \u001b[38;5;66;03m# type: ignore[arg-type]\u001b[39;00m\n\u001b[1;32m    521\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIncremented Retry for (url=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m): \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, url, new_retry)\n",
      "\u001b[0;31mMaxRetryError\u001b[0m: HTTPSConnectionPool(host='huggingface.co', port=443): Max retries exceeded with url: /BAAI/bge-en-icl/resolve/main/model-00001-of-00003.safetensors (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x7fcefad9e2a0>, 'Connection to huggingface.co timed out. (connect timeout=10)'))",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mConnectTimeout\u001b[0m                            Traceback (most recent call last)",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/huggingface_hub/file_download.py:1376\u001b[0m, in \u001b[0;36m_get_metadata_or_catch_error\u001b[0;34m(repo_id, filename, repo_type, revision, endpoint, proxies, etag_timeout, headers, token, local_files_only, relative_filename, storage_folder)\u001b[0m\n\u001b[1;32m   1375\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1376\u001b[0m     metadata \u001b[38;5;241m=\u001b[39m \u001b[43mget_hf_file_metadata\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1377\u001b[0m \u001b[43m        \u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mproxies\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mproxies\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43metag_timeout\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtoken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoken\u001b[49m\n\u001b[1;32m   1378\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1379\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m EntryNotFoundError \u001b[38;5;28;01mas\u001b[39;00m http_error:\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/huggingface_hub/utils/_validators.py:114\u001b[0m, in \u001b[0;36mvalidate_hf_hub_args.<locals>._inner_fn\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    112\u001b[0m     kwargs \u001b[38;5;241m=\u001b[39m smoothly_deprecate_use_auth_token(fn_name\u001b[38;5;241m=\u001b[39mfn\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, has_token\u001b[38;5;241m=\u001b[39mhas_token, kwargs\u001b[38;5;241m=\u001b[39mkwargs)\n\u001b[0;32m--> 114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/huggingface_hub/file_download.py:1296\u001b[0m, in \u001b[0;36mget_hf_file_metadata\u001b[0;34m(url, token, proxies, timeout, library_name, library_version, user_agent, headers)\u001b[0m\n\u001b[1;32m   1295\u001b[0m \u001b[38;5;66;03m# Retrieve metadata\u001b[39;00m\n\u001b[0;32m-> 1296\u001b[0m r \u001b[38;5;241m=\u001b[39m \u001b[43m_request_wrapper\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1297\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mHEAD\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1298\u001b[0m \u001b[43m    \u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1299\u001b[0m \u001b[43m    \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1300\u001b[0m \u001b[43m    \u001b[49m\u001b[43mallow_redirects\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m   1301\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfollow_relative_redirects\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m   1302\u001b[0m \u001b[43m    \u001b[49m\u001b[43mproxies\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mproxies\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1303\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1304\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1305\u001b[0m hf_raise_for_status(r)\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/huggingface_hub/file_download.py:277\u001b[0m, in \u001b[0;36m_request_wrapper\u001b[0;34m(method, url, follow_relative_redirects, **params)\u001b[0m\n\u001b[1;32m    276\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m follow_relative_redirects:\n\u001b[0;32m--> 277\u001b[0m     response \u001b[38;5;241m=\u001b[39m \u001b[43m_request_wrapper\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    278\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    279\u001b[0m \u001b[43m        \u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    280\u001b[0m \u001b[43m        \u001b[49m\u001b[43mfollow_relative_redirects\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    281\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    282\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    284\u001b[0m     \u001b[38;5;66;03m# If redirection, we redirect only relative paths.\u001b[39;00m\n\u001b[1;32m    285\u001b[0m     \u001b[38;5;66;03m# This is useful in case of a renamed repository.\u001b[39;00m\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/huggingface_hub/file_download.py:300\u001b[0m, in \u001b[0;36m_request_wrapper\u001b[0;34m(method, url, follow_relative_redirects, **params)\u001b[0m\n\u001b[1;32m    299\u001b[0m \u001b[38;5;66;03m# Perform request and return if status_code is not in the retry list.\u001b[39;00m\n\u001b[0;32m--> 300\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[43mget_session\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    301\u001b[0m hf_raise_for_status(response)\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/requests/sessions.py:589\u001b[0m, in \u001b[0;36mSession.request\u001b[0;34m(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)\u001b[0m\n\u001b[1;32m    588\u001b[0m send_kwargs\u001b[38;5;241m.\u001b[39mupdate(settings)\n\u001b[0;32m--> 589\u001b[0m resp \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mprep\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43msend_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    591\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m resp\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/requests/sessions.py:703\u001b[0m, in \u001b[0;36mSession.send\u001b[0;34m(self, request, **kwargs)\u001b[0m\n\u001b[1;32m    702\u001b[0m \u001b[38;5;66;03m# Send the request\u001b[39;00m\n\u001b[0;32m--> 703\u001b[0m r \u001b[38;5;241m=\u001b[39m \u001b[43madapter\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    705\u001b[0m \u001b[38;5;66;03m# Total elapsed time of the request (approximately)\u001b[39;00m\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/huggingface_hub/utils/_http.py:93\u001b[0m, in \u001b[0;36mUniqueRequestIdAdapter.send\u001b[0;34m(self, request, *args, **kwargs)\u001b[0m\n\u001b[1;32m     92\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 93\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     94\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m requests\u001b[38;5;241m.\u001b[39mRequestException \u001b[38;5;28;01mas\u001b[39;00m e:\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/requests/adapters.py:688\u001b[0m, in \u001b[0;36mHTTPAdapter.send\u001b[0;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[1;32m    687\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(e\u001b[38;5;241m.\u001b[39mreason, NewConnectionError):\n\u001b[0;32m--> 688\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m ConnectTimeout(e, request\u001b[38;5;241m=\u001b[39mrequest)\n\u001b[1;32m    690\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(e\u001b[38;5;241m.\u001b[39mreason, ResponseError):\n",
      "\u001b[0;31mConnectTimeout\u001b[0m: (MaxRetryError(\"HTTPSConnectionPool(host='huggingface.co', port=443): Max retries exceeded with url: /BAAI/bge-en-icl/resolve/main/model-00001-of-00003.safetensors (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x7fcefad9e2a0>, 'Connection to huggingface.co timed out. (connect timeout=10)'))\"), '(Request ID: 7e63b258-fd0e-43b5-9fff-45352324af0b)')",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mLocalEntryNotFoundError\u001b[0m                   Traceback (most recent call last)",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/transformers/utils/hub.py:403\u001b[0m, in \u001b[0;36mcached_file\u001b[0;34m(path_or_repo_id, filename, cache_dir, force_download, resume_download, proxies, token, revision, local_files_only, subfolder, repo_type, user_agent, _raise_exceptions_for_gated_repo, _raise_exceptions_for_missing_entries, _raise_exceptions_for_connection_errors, _commit_hash, **deprecated_kwargs)\u001b[0m\n\u001b[1;32m    401\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m    402\u001b[0m     \u001b[38;5;66;03m# Load from URL or cache if already cached\u001b[39;00m\n\u001b[0;32m--> 403\u001b[0m     resolved_file \u001b[38;5;241m=\u001b[39m \u001b[43mhf_hub_download\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    404\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpath_or_repo_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    405\u001b[0m \u001b[43m        \u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    406\u001b[0m \u001b[43m        \u001b[49m\u001b[43msubfolder\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43msubfolder\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m==\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43msubfolder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    407\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrepo_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    408\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrevision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrevision\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    409\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcache_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    410\u001b[0m \u001b[43m        \u001b[49m\u001b[43muser_agent\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muser_agent\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    411\u001b[0m \u001b[43m        \u001b[49m\u001b[43mforce_download\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mforce_download\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    412\u001b[0m \u001b[43m        \u001b[49m\u001b[43mproxies\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mproxies\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    413\u001b[0m \u001b[43m        \u001b[49m\u001b[43mresume_download\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mresume_download\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    414\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtoken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    415\u001b[0m \u001b[43m        \u001b[49m\u001b[43mlocal_files_only\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlocal_files_only\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    416\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    417\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m GatedRepoError \u001b[38;5;28;01mas\u001b[39;00m e:\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/huggingface_hub/utils/_validators.py:114\u001b[0m, in \u001b[0;36mvalidate_hf_hub_args.<locals>._inner_fn\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    112\u001b[0m     kwargs \u001b[38;5;241m=\u001b[39m smoothly_deprecate_use_auth_token(fn_name\u001b[38;5;241m=\u001b[39mfn\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, has_token\u001b[38;5;241m=\u001b[39mhas_token, kwargs\u001b[38;5;241m=\u001b[39mkwargs)\n\u001b[0;32m--> 114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/huggingface_hub/file_download.py:862\u001b[0m, in \u001b[0;36mhf_hub_download\u001b[0;34m(repo_id, filename, subfolder, repo_type, revision, library_name, library_version, cache_dir, local_dir, user_agent, force_download, proxies, etag_timeout, token, local_files_only, headers, endpoint, resume_download, force_filename, local_dir_use_symlinks)\u001b[0m\n\u001b[1;32m    861\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 862\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_hf_hub_download_to_cache_dir\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    863\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;66;43;03m# Destination\u001b[39;49;00m\n\u001b[1;32m    864\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcache_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    865\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;66;43;03m# File info\u001b[39;49;00m\n\u001b[1;32m    866\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrepo_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    867\u001b[0m \u001b[43m        \u001b[49m\u001b[43mfilename\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    868\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrepo_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    869\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrevision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrevision\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    870\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;66;43;03m# HTTP info\u001b[39;49;00m\n\u001b[1;32m    871\u001b[0m \u001b[43m        \u001b[49m\u001b[43mendpoint\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mendpoint\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    872\u001b[0m \u001b[43m        \u001b[49m\u001b[43metag_timeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43metag_timeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    873\u001b[0m \u001b[43m        \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    874\u001b[0m \u001b[43m        \u001b[49m\u001b[43mproxies\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mproxies\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    875\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtoken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    876\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;66;43;03m# Additional options\u001b[39;49;00m\n\u001b[1;32m    877\u001b[0m \u001b[43m        \u001b[49m\u001b[43mlocal_files_only\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlocal_files_only\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    878\u001b[0m \u001b[43m        \u001b[49m\u001b[43mforce_download\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mforce_download\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    879\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/huggingface_hub/file_download.py:969\u001b[0m, in \u001b[0;36m_hf_hub_download_to_cache_dir\u001b[0;34m(cache_dir, repo_id, filename, repo_type, revision, endpoint, etag_timeout, headers, proxies, token, local_files_only, force_download)\u001b[0m\n\u001b[1;32m    968\u001b[0m     \u001b[38;5;66;03m# Otherwise, raise appropriate error\u001b[39;00m\n\u001b[0;32m--> 969\u001b[0m     \u001b[43m_raise_on_head_call_error\u001b[49m\u001b[43m(\u001b[49m\u001b[43mhead_call_error\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mforce_download\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlocal_files_only\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    971\u001b[0m \u001b[38;5;66;03m# From now on, etag, commit_hash, url and size are not None.\u001b[39;00m\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/huggingface_hub/file_download.py:1487\u001b[0m, in \u001b[0;36m_raise_on_head_call_error\u001b[0;34m(head_call_error, force_download, local_files_only)\u001b[0m\n\u001b[1;32m   1485\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   1486\u001b[0m     \u001b[38;5;66;03m# Otherwise: most likely a connection issue or Hub downtime => let's warn the user\u001b[39;00m\n\u001b[0;32m-> 1487\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m LocalEntryNotFoundError(\n\u001b[1;32m   1488\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAn error happened while trying to locate the file on the Hub and we cannot find the requested files\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1489\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m in the local cache. Please check your connection and try again or make sure your Internet connection\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1490\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m is on.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1491\u001b[0m     ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mhead_call_error\u001b[39;00m\n",
      "\u001b[0;31mLocalEntryNotFoundError\u001b[0m: An error happened while trying to locate the file on the Hub and we cannot find the requested files in the local cache. Please check your connection and try again or make sure your Internet connection is on.",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[8], line 6\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mos\u001b[39;00m\n\u001b[1;32m      4\u001b[0m os\u001b[38;5;241m.\u001b[39menviron[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mHF_ENDPOINT\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhttps://hf-mirror.com\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m----> 6\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[43mFlagICLModel\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mBAAI/bge-en-icl\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m      7\u001b[0m \u001b[43m                     \u001b[49m\u001b[43mexamples_for_task\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mexamples\u001b[49m\u001b[43m,\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# set `examples_for_task=None` to use model without examples\u001b[39;49;00m\n\u001b[1;32m      8\u001b[0m \u001b[43m                     \u001b[49m\u001b[43mexamples_instruction_format\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m<instruct>\u001b[39;49m\u001b[38;5;132;43;01m{}\u001b[39;49;00m\u001b[38;5;130;43;01m\\n\u001b[39;49;00m\u001b[38;5;124;43m<query>\u001b[39;49m\u001b[38;5;132;43;01m{}\u001b[39;49;00m\u001b[38;5;130;43;01m\\n\u001b[39;49;00m\u001b[38;5;124;43m<response>\u001b[39;49m\u001b[38;5;132;43;01m{}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# specify the format to use examples_for_task\u001b[39;49;00m\n\u001b[1;32m      9\u001b[0m \u001b[43m                     \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     11\u001b[0m embeddings_1 \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mencode_queries(queries)\n\u001b[1;32m     12\u001b[0m embeddings_2 \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mencode_corpus(documents)\n",
      "File \u001b[0;32m/share/project/xzy/working/FlagEmbedding/FlagEmbedding/inference/embedder/decoder_only/icl.py:57\u001b[0m, in \u001b[0;36mICLLLMEmbedder.__init__\u001b[0;34m(self, model_name_or_path, normalize_embeddings, use_fp16, query_instruction_for_retrieval, query_instruction_format, devices, examples_for_task, examples_instruction_format, trust_remote_code, cache_dir, **kwargs)\u001b[0m\n\u001b[1;32m     42\u001b[0m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m     43\u001b[0m     model_name_or_path,\n\u001b[1;32m     44\u001b[0m     normalize_embeddings\u001b[38;5;241m=\u001b[39mnormalize_embeddings,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     49\u001b[0m     kwargs\u001b[38;5;241m=\u001b[39mkwargs\n\u001b[1;32m     50\u001b[0m )\n\u001b[1;32m     52\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtokenizer \u001b[38;5;241m=\u001b[39m AutoTokenizer\u001b[38;5;241m.\u001b[39mfrom_pretrained(\n\u001b[1;32m     53\u001b[0m     model_name_or_path,\n\u001b[1;32m     54\u001b[0m     trust_remote_code\u001b[38;5;241m=\u001b[39mtrust_remote_code,\n\u001b[1;32m     55\u001b[0m     cache_dir\u001b[38;5;241m=\u001b[39mcache_dir\n\u001b[1;32m     56\u001b[0m )\n\u001b[0;32m---> 57\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel \u001b[38;5;241m=\u001b[39m \u001b[43mAutoModel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_pretrained\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     58\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmodel_name_or_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     59\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtrust_remote_code\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtrust_remote_code\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     60\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcache_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_dir\u001b[49m\n\u001b[1;32m     61\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     62\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mexamples_for_task \u001b[38;5;241m=\u001b[39m examples_for_task\n\u001b[1;32m     63\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mexamples_instruction_format \u001b[38;5;241m=\u001b[39m examples_instruction_format\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/transformers/models/auto/auto_factory.py:564\u001b[0m, in \u001b[0;36m_BaseAutoModelClass.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m    562\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(config) \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping\u001b[38;5;241m.\u001b[39mkeys():\n\u001b[1;32m    563\u001b[0m     model_class \u001b[38;5;241m=\u001b[39m _get_model_class(config, \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping)\n\u001b[0;32m--> 564\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmodel_class\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_pretrained\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    565\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpretrained_model_name_or_path\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mmodel_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mhub_kwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\n\u001b[1;32m    566\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    567\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    568\u001b[0m     \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnrecognized configuration class \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mconfig\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m for this kind of AutoModel: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    569\u001b[0m     \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mModel type should be one of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(c\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mfor\u001b[39;00m\u001b[38;5;250m \u001b[39mc\u001b[38;5;250m \u001b[39m\u001b[38;5;129;01min\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping\u001b[38;5;241m.\u001b[39mkeys())\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    570\u001b[0m )\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/transformers/modeling_utils.py:3769\u001b[0m, in \u001b[0;36mPreTrainedModel.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m   3766\u001b[0m \u001b[38;5;66;03m# We'll need to download and cache each checkpoint shard if the checkpoint is sharded.\u001b[39;00m\n\u001b[1;32m   3767\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_sharded:\n\u001b[1;32m   3768\u001b[0m     \u001b[38;5;66;03m# resolved_archive_file becomes a list of files that point to the different checkpoint shards in this case.\u001b[39;00m\n\u001b[0;32m-> 3769\u001b[0m     resolved_archive_file, sharded_metadata \u001b[38;5;241m=\u001b[39m \u001b[43mget_checkpoint_shard_files\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   3770\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpretrained_model_name_or_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3771\u001b[0m \u001b[43m        \u001b[49m\u001b[43mresolved_archive_file\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3772\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcache_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3773\u001b[0m \u001b[43m        \u001b[49m\u001b[43mforce_download\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mforce_download\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3774\u001b[0m \u001b[43m        \u001b[49m\u001b[43mproxies\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mproxies\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3775\u001b[0m \u001b[43m        \u001b[49m\u001b[43mresume_download\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mresume_download\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3776\u001b[0m \u001b[43m        \u001b[49m\u001b[43mlocal_files_only\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlocal_files_only\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3777\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtoken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3778\u001b[0m \u001b[43m        \u001b[49m\u001b[43muser_agent\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muser_agent\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3779\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrevision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrevision\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3780\u001b[0m \u001b[43m        \u001b[49m\u001b[43msubfolder\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msubfolder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3781\u001b[0m \u001b[43m        \u001b[49m\u001b[43m_commit_hash\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcommit_hash\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3782\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3784\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\n\u001b[1;32m   3785\u001b[0m     is_safetensors_available()\n\u001b[1;32m   3786\u001b[0m     \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(resolved_archive_file, \u001b[38;5;28mstr\u001b[39m)\n\u001b[1;32m   3787\u001b[0m     \u001b[38;5;129;01mand\u001b[39;00m resolved_archive_file\u001b[38;5;241m.\u001b[39mendswith(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.safetensors\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m   3788\u001b[0m ):\n\u001b[1;32m   3789\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m safe_open(resolved_archive_file, framework\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpt\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m f:\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/transformers/utils/hub.py:1098\u001b[0m, in \u001b[0;36mget_checkpoint_shard_files\u001b[0;34m(pretrained_model_name_or_path, index_filename, cache_dir, force_download, proxies, resume_download, local_files_only, token, user_agent, revision, subfolder, _commit_hash, **deprecated_kwargs)\u001b[0m\n\u001b[1;32m   1095\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m shard_filename \u001b[38;5;129;01min\u001b[39;00m tqdm(shard_filenames, desc\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDownloading shards\u001b[39m\u001b[38;5;124m\"\u001b[39m, disable\u001b[38;5;241m=\u001b[39m\u001b[38;5;129;01mnot\u001b[39;00m show_progress_bar):\n\u001b[1;32m   1096\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m   1097\u001b[0m         \u001b[38;5;66;03m# Load from URL\u001b[39;00m\n\u001b[0;32m-> 1098\u001b[0m         cached_filename \u001b[38;5;241m=\u001b[39m \u001b[43mcached_file\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1099\u001b[0m \u001b[43m            \u001b[49m\u001b[43mpretrained_model_name_or_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1100\u001b[0m \u001b[43m            \u001b[49m\u001b[43mshard_filename\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1101\u001b[0m \u001b[43m            \u001b[49m\u001b[43mcache_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1102\u001b[0m \u001b[43m            \u001b[49m\u001b[43mforce_download\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mforce_download\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1103\u001b[0m \u001b[43m            \u001b[49m\u001b[43mproxies\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mproxies\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1104\u001b[0m \u001b[43m            \u001b[49m\u001b[43mresume_download\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mresume_download\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1105\u001b[0m \u001b[43m            \u001b[49m\u001b[43mlocal_files_only\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlocal_files_only\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1106\u001b[0m \u001b[43m            \u001b[49m\u001b[43mtoken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1107\u001b[0m \u001b[43m            \u001b[49m\u001b[43muser_agent\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muser_agent\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1108\u001b[0m \u001b[43m            \u001b[49m\u001b[43mrevision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrevision\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1109\u001b[0m \u001b[43m            \u001b[49m\u001b[43msubfolder\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msubfolder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1110\u001b[0m \u001b[43m            \u001b[49m\u001b[43m_commit_hash\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m_commit_hash\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1111\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1112\u001b[0m     \u001b[38;5;66;03m# We have already dealt with RepositoryNotFoundError and RevisionNotFoundError when getting the index, so\u001b[39;00m\n\u001b[1;32m   1113\u001b[0m     \u001b[38;5;66;03m# we don't have to catch them here.\u001b[39;00m\n\u001b[1;32m   1114\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m EntryNotFoundError:\n",
      "File \u001b[0;32m~/anaconda3/envs/dev/lib/python3.12/site-packages/transformers/utils/hub.py:446\u001b[0m, in \u001b[0;36mcached_file\u001b[0;34m(path_or_repo_id, filename, cache_dir, force_download, resume_download, proxies, token, revision, local_files_only, subfolder, repo_type, user_agent, _raise_exceptions_for_gated_repo, _raise_exceptions_for_missing_entries, _raise_exceptions_for_connection_errors, _commit_hash, **deprecated_kwargs)\u001b[0m\n\u001b[1;32m    440\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m (\n\u001b[1;32m    441\u001b[0m         resolved_file \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m    442\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m _raise_exceptions_for_missing_entries\n\u001b[1;32m    443\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m _raise_exceptions_for_connection_errors\n\u001b[1;32m    444\u001b[0m     ):\n\u001b[1;32m    445\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m resolved_file\n\u001b[0;32m--> 446\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mEnvironmentError\u001b[39;00m(\n\u001b[1;32m    447\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mWe couldn\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt connect to \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mHUGGINGFACE_CO_RESOLVE_ENDPOINT\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m to load this file, couldn\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt find it in the\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    448\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m cached files and it looks like \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpath_or_repo_id\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m is not the path to a directory containing a file named\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    449\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfull_filename\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124mCheckout your internet connection or see how to run the library in offline mode at\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    450\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhttps://huggingface.co/docs/transformers/installation#offline-mode\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    451\u001b[0m     ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n\u001b[1;32m    452\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m EntryNotFoundError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    453\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m _raise_exceptions_for_missing_entries:\n",
      "\u001b[0;31mOSError\u001b[0m: We couldn't connect to 'https://huggingface.co' to load this file, couldn't find it in the cached files and it looks like BAAI/bge-en-icl is not the path to a directory containing a file named model-00001-of-00003.safetensors.\nCheckout your internet connection or see how to run the library in offline mode at 'https://huggingface.co/docs/transformers/installation#offline-mode'."
     ]
    }
   ],
   "source": [
    "from FlagEmbedding import FlagICLModel\n",
    "import os\n",
    "\n",
    "os.environ['HF_ENDPOINT']='https://hf-mirror.com'\n",
    "\n",
    "model = FlagICLModel('BAAI/bge-en-icl', \n",
    "                     examples_for_task=examples,  # set `examples_for_task=None` to use model without examples\n",
    "                     examples_instruction_format=\"<instruct>{}\\n<query>{}\\n<response>{}\" # specify the format to use examples_for_task\n",
    "                     )\n",
    "\n",
    "embeddings_1 = model.encode_queries(queries)\n",
    "embeddings_2 = model.encode_corpus(documents)\n",
    "similarity = embeddings_1 @ embeddings_2.T\n",
    "\n",
    "print(similarity)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dda52b9a",
   "metadata": {},
   "source": []
  }
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   "language": "python",
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    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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