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fixed typos (#414)

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* fixed typos

* fixed formatting

* Update ch03/02_bonus_efficient-multihead-attention/mha-implementations.ipynb

* del weights after load into model

---------

Co-authored-by: Sebastian Raschka <mail@sebastianraschka.com>
This commit is contained in:
Daniel Kleine 2024-10-25 01:23:53 +02:00 committed by GitHub
parent 8b60460319
commit 0ed1e0d099
2 changed files with 18 additions and 14 deletions
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20
ch03/02_bonus_efficient-multihead-attention/mha-implementations.ipynb
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@ -83,8 +83,8 @@
},
"source": [
"- To run all the code in this notebook, please ensure you update to at least PyTorch 2.5 (FlexAttention is not included in earlier PyTorch releases)\n",
"If the code cell above shows a PyTorch version lower than 2.5, you can upgrade your PyTorch installation by uncommenting and running the following code cell (Please note that PyTorch 2.5 requires Python 3.9 or later)\n",
"- For more specific instructions and CUDA versions, please refer to the official installation guide at https://pytorch.org."
"- If the code cell above shows a PyTorch version lower than 2.5, you can upgrade your PyTorch installation by uncommenting and running the following code cell (Please note that PyTorch 2.5 requires Python 3.9 or later)\n",
"- For more specific instructions and CUDA versions, please refer to the official installation guide at https://pytorch.org"
]
},
{
@ -886,12 +886,14 @@
"id": "d2164859-31a0-4537-b4fb-27d57675ba77"
},
"source": [
"- Set `need_weights` (default `True`) to need_weights=False so that `MultiheadAttention` uses `scaled_dot_product_attention` [according to the documentation](https://github.com/pytorch/pytorch/blob/71d020262793542974cf13b30f2a9099773f015c/torch/nn/modules/activation.py#L1096)\n",
"- Set `need_weights` (default `True`) to `False` so that `MultiheadAttention` uses `scaled_dot_product_attention` [according to the documentation](https://github.com/pytorch/pytorch/blob/71d020262793542974cf13b30f2a9099773f015c/torch/nn/modules/activation.py#L1096)\n",
"\n",
"> need_weights: If specified, returns ``attn_output_weights`` in addition to ``attn_outputs``.\n",
" Set ``need_weights=False`` to use the optimized ``scaled_dot_product_attention``\n",
" and achieve the best performance for MHA.\n",
" Default: ``True``."
"```markdown\n",
"need_weights: If specified, returns `attn_output_weights` in addition to `attn_outputs`.\n",
" Set `need_weights=False` to use the optimized `scaled_dot_product_attention`\n",
" and achieve the best performance for MHA.\n",
" Default: `True`\n",
"```"
]
},
{
@ -1965,7 +1967,7 @@
"provenance": []
},
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "pt",
"language": "python",
"name": "python3"
},
@ -1979,7 +1981,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.4"
"version": "3.11.9"
}
},
"nbformat": 4,

12
ch05/07_gpt_to_llama/converting-llama2-to-llama3.ipynb
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@ -1843,7 +1843,7 @@
"id": "VlH7qYVdDKQr"
},
"source": [
"- Note that the Llama 3 model should ideally used with the correct prompt template that was used during finetuning (as discussed in chapter 7)\n",
"- Note that the Llama 3 model should ideally be used with the correct prompt template that was used during finetuning (as discussed in chapter 7)\n",
"- Below is a wrapper class around the tokenizer based on Meta AI's Llama 3-specific [ChatFormat code](https://github.com/meta-llama/llama3/blob/11817d47e1ba7a4959b025eb1ca308572e0e3963/llama/tokenizer.py#L202) that constructs the prompt template"
]
},
@ -2099,7 +2099,7 @@
"metadata": {},
"outputs": [],
"source": [
"LLAMA32_CONFIG[\"context_length\"] = 8192"
"LLAMA31_CONFIG_8B[\"context_length\"] = 8192"
]
},
{
@ -2319,7 +2319,8 @@
" combined_weights.update(current_weights)\n",
"\n",
"load_weights_into_llama(model, LLAMA31_CONFIG_8B, combined_weights)\n",
"model.to(device);"
"model.to(device);\n",
"del combined_weights # free up memory"
]
},
{
@ -2466,7 +2467,7 @@
"metadata": {},
"outputs": [],
"source": [
"LLAMA32_CONFIG[\"context_length\"] = 8192"
"LLAMA32_CONFIG_1B[\"context_length\"] = 8192"
]
},
{
@ -2594,7 +2595,8 @@
"current_weights = load_file(weights_file)\n",
"\n",
"load_weights_into_llama(model, LLAMA32_CONFIG_1B, current_weights)\n",
"model.to(device);"
"model.to(device);\n",
"del current_weights # free up memory"
]
},
{