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  - alpaca
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  ---
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  ### Stanford Alpaca-7B
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- This repo hosts the merged weight for [Stanford Alpaca-7B](https://github.com/tatsu-lab/stanford_alpaca/) that can be used directly.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - alpaca
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  ---
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+ ### Stanford Alpaca-7B-Merged
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+
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+ This repo hosts the merged weight for [Stanford Alpaca-7B](https://github.com/tatsu-lab/stanford_alpaca/) that can be used directly.
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+ Below is the original model card information.
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+
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+ -----------------------
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  ### Stanford Alpaca-7B
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+ This repo hosts the weight diff for [Stanford Alpaca-7B](https://github.com/tatsu-lab/stanford_alpaca/) that can be used to reconstruct the original model weights when applied to Meta's LLaMA weights.
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+
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+ To recover the original Alpaca-7B weights, follow these steps:
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+ ```text
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+ 1. Convert Meta's released weights into huggingface format. Follow this guide:
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+ https://huggingface.co/docs/transformers/main/model_doc/llama
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+ 2. Make sure you cloned the released weight diff into your local machine. The weight diff is located at:
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+ https://huggingface.co/tatsu-lab/alpaca-7b/tree/main
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+ 3. Run this function with the correct paths. E.g.,
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+ python weight_diff.py recover --path_raw <path_to_step_1_dir> --path_diff <path_to_step_2_dir> --path_tuned <path_to_store_recovered_weights>
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+ ```
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+
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+ Once step 3 completes, you should have a directory with the recovered weights, from which you can load the model like the following
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+
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+ ```python
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+ import transformers
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+ alpaca_model = transformers.AutoModelForCausalLM.from_pretrained("<path_to_store_recovered_weights>")
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+ alpaca_tokenizer = transformers.AutoTokenizer.from_pretrained("<path_to_store_recovered_weights>")
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+ ```