alpaca-7b-merged

Stanford Alpaca-7B-Merged

The weight file is split into chunks with a size of 405M for convenient and fast parallel downloads

This repo hosts the merged weight for Stanford Alpaca-7B that can be used directly. Below is the original model card information.

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Stanford Alpaca-7B

This repo hosts the weight diff for Stanford Alpaca-7B that can be used to reconstruct the original model weights when applied to Meta's LLaMA weights.

To recover the original Alpaca-7B weights, follow these steps:

1. Convert Meta's released weights into huggingface format. Follow this guide:
    https://huggingface.co/docs/transformers/main/model_doc/llama
2. Make sure you cloned the released weight diff into your local machine. The weight diff is located at:
    https://huggingface.co/tatsu-lab/alpaca-7b/tree/main
3. Run this function with the correct paths. E.g.,
    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>

Once step 3 completes, you should have a directory with the recovered weights, from which you can load the model like the following

import transformers
alpaca_model = transformers.AutoModelForCausalLM.from_pretrained("<path_to_store_recovered_weights>")
alpaca_tokenizer = transformers.AutoTokenizer.from_pretrained("<path_to_store_recovered_weights>")