add the code of ch07

Codes/ch07/01_main-chapter-code/README.md

@@ -0,0 +1,76 @@
+# Chapter 7: Finetuning to Follow Instructions
+
+### Main Chapter Code
+
+- [ch07.ipynb](ch07.ipynb) contains all the code as it appears in the chapter
+- [previous_chapters.py](previous_chapters.py) is a Python module that contains the GPT model we coded and trained in previous chapters, alongside many utility functions, which we reuse in this chapter
+- [gpt_download.py](gpt_download.py) contains the utility functions for downloading the pretrained GPT model weights
+- [exercise-solutions.ipynb](exercise-solutions.ipynb) contains the exercise solutions for this chapter
+
+
+### Optional Code
+
+- [load-finetuned-model.ipynb](load-finetuned-model.ipynb) is a standalone Jupyter notebook to load the instruction finetuned model we created in this chapter
+
+- [gpt_instruction_finetuning.py](gpt_instruction_finetuning.py) is a standalone Python script to instruction finetune the model as described in the main chapter (think of it as a chapter summary focused on the finetuning parts)
+
+Usage:
+
+```bash
+python gpt_instruction_finetuning.py
+```
+
+```
+matplotlib version: 3.9.0
+tiktoken version: 0.7.0
+torch version: 2.3.1
+tqdm version: 4.66.4
+tensorflow version: 2.16.1
+--------------------------------------------------
+Training set length: 935
+Validation set length: 55
+Test set length: 110
+--------------------------------------------------
+Device: cpu
+--------------------------------------------------
+File already exists and is up-to-date: gpt2/355M/checkpoint
+File already exists and is up-to-date: gpt2/355M/encoder.json
+File already exists and is up-to-date: gpt2/355M/hparams.json
+File already exists and is up-to-date: gpt2/355M/model.ckpt.data-00000-of-00001
+File already exists and is up-to-date: gpt2/355M/model.ckpt.index
+File already exists and is up-to-date: gpt2/355M/model.ckpt.meta
+File already exists and is up-to-date: gpt2/355M/vocab.bpe
+Loaded model: gpt2-medium (355M)
+--------------------------------------------------
+Initial losses
+   Training loss: 3.839039182662964
+   Validation loss: 3.7619192123413088
+Ep 1 (Step 000000): Train loss 2.611, Val loss 2.668
+Ep 1 (Step 000005): Train loss 1.161, Val loss 1.131
+Ep 1 (Step 000010): Train loss 0.939, Val loss 0.973
+...
+Training completed in 15.66 minutes.
+Plot saved as loss-plot-standalone.pdf
+--------------------------------------------------
+Generating responses
+100%|█████████████████████████████████████████████████████████| 110/110 [06:57<00:00,  3.80s/it]
+Responses saved as instruction-data-with-response-standalone.json
+Model saved as gpt2-medium355M-sft-standalone.pth
+```
+
+- [ollama_evaluate.py](ollama_evaluate.py) is a standalone Python script to evaluate the responses of the finetuned model as described in the main chapter (think of it as a chapter summary focused on the evaluation parts)
+
+Usage:
+
+```bash
+python ollama_evaluate.py --file_path instruction-data-with-response-standalone.json
+```
+
+```
+Ollama running: True
+Scoring entries: 100%|███████████████████████████████████████| 110/110 [01:08<00:00,  1.62it/s]
+Number of scores: 110 of 110
+Average score: 51.75
+```
+
+- [exercise_experiments.py](exercise_experiments.py) is an optional scropt that implements the exercise solutions; for more details see [exercise-solutions.ipynb](exercise-solutions.ipynb)