From ce80a192cd4c0e54abc7dfeaf906efc81111b6b4 Mon Sep 17 00:00:00 2001 From: rasbt Date: Tue, 27 Aug 2024 08:26:40 +0200 Subject: [PATCH] refresh figures --- ch07/01_main-chapter-code/ch07.ipynb | 30 ++++++++++++++-------------- 1 file changed, 15 insertions(+), 15 deletions(-) diff --git a/ch07/01_main-chapter-code/ch07.ipynb b/ch07/01_main-chapter-code/ch07.ipynb index 1db0a3d..a4652a2 100644 --- a/ch07/01_main-chapter-code/ch07.ipynb +++ b/ch07/01_main-chapter-code/ch07.ipynb @@ -16,7 +16,7 @@ "\n", "\n", "\n", - "\n", + "\n", "\n", "\n", "" @@ -77,7 +77,7 @@ "id": "264fca98-2f9a-4193-b435-2abfa3b4142f" }, "source": [ - "" + "" ] }, { @@ -121,7 +121,7 @@ "source": [ "- The topics covered in this chapter are summarized in the figure below\n", "\n", - "" + "" ] }, { @@ -285,7 +285,7 @@ "id": "dffa4f70-44d4-4be4-89a9-2159f4885b10" }, "source": [ - "" + "" ] }, { @@ -482,7 +482,7 @@ "id": "233f63bd-9755-4d07-8884-5e2e5345cf27" }, "source": [ - "" + "" ] }, { @@ -709,7 +709,7 @@ "id": "0386b6fe-3455-4e70-becd-a5a4681ba2ef" }, "source": [ - "" + "" ] }, { @@ -804,7 +804,7 @@ "id": "bd4bed33-956e-4b3f-a09c-586d8203109a" }, "source": [ - "" + "" ] }, { @@ -1058,7 +1058,7 @@ "id": "fab8f0ed-80e8-4fd9-bf84-e5d0e0bc0a39" }, "source": [ - "" + "" ] }, { @@ -1088,7 +1088,7 @@ "id": "9fffe390-b226-4d5c-983f-9f4da773cb82" }, "source": [ - "" + "" ] }, { @@ -1488,7 +1488,7 @@ "id": "8d1b438f-88af-413f-96a9-f059c6c55fc4" }, "source": [ - "" + "" ] }, { @@ -1706,7 +1706,7 @@ "source": [ "- In this section, we finetune the model\n", "\n", - "\n", + "\n", "\n", "- Note that we can reuse all the loss calculation and training functions that we used in previous chapters" ] @@ -1968,7 +1968,7 @@ "id": "5a25cc88-1758-4dd0-b8bf-c044cbf2dd49" }, "source": [ - "" + "" ] }, { @@ -2224,7 +2224,7 @@ "id": "805b9d30-7336-499f-abb5-4a21be3129f5" }, "source": [ - "" + "" ] }, { @@ -2264,7 +2264,7 @@ "\n", "- In general, before we can use ollama from the command line, we have to either start the ollama application or run `ollama serve` in a separate terminal\n", "\n", - "\n", + "\n", "\n", "\n", "- With the ollama application or `ollama serve` running in a different terminal, on the command line, execute the following command to try out the 8-billion-parameter Llama 3 model (the model, which takes up 4.7 GB of storage space, will be automatically downloaded the first time you execute this command)\n", @@ -2710,7 +2710,7 @@ "- This marks the final chapter of this book\n", "- We covered the major steps of the LLM development cycle: implementing an LLM architecture, pretraining an LLM, and finetuning it\n", "\n", - "\n", + "\n", "\n", "- An optional step that is sometimes followed after instruction finetuning, as described in this chapter, is preference finetuning\n", "- Preference finetuning process can be particularly useful for customizing a model to better align with specific user preferences; see the [../04_preference-tuning-with-dpo](../04_preference-tuning-with-dpo) folder if you are interested in this\n",