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Update README.md

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@@ -32,7 +32,7 @@ This model was built via parameter-efficient finetuning of the [mistralai/Mistra
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  ## Model Sources
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- - **Repository:** [github.com/daniel-furman/sft-demos](https://github.com/daniel-furman/sft-demos/blob/main/src/sft/one_gpu/mistral/sft-mistral-7b-instruct-peft.ipynb)
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  ## Evaluation Results
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@@ -209,6 +209,8 @@ print(tokenizer.decode(input_ids[0]))
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  We use the [SFTTrainer](https://huggingface.co/docs/trl/main/en/sft_trainer) from `trl` to fine-tune LLMs on instruction-following datasets.
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  The following `TrainingArguments` config was used:
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  - num_train_epochs = 1
 
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  ## Model Sources
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+ - **Repository:** [github.com/daniel-furman/sft-demos](https://github.com/daniel-furman/sft-demos/blob/main/src/sft/mistral/sft_Mistral_7B_Instruct_v0_1_peft.ipynb)
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  ## Evaluation Results
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  We use the [SFTTrainer](https://huggingface.co/docs/trl/main/en/sft_trainer) from `trl` to fine-tune LLMs on instruction-following datasets.
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+ See [here](https://github.com/daniel-furman/sft-demos/blob/main/src/sft/mistral/sft_Mistral_7B_Instruct_v0_1_peft.ipynb) for the finetuning code, which contains an exhaustive view of the hyperparameters employed.
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  The following `TrainingArguments` config was used:
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  - num_train_epochs = 1