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README.md
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The weight of `word embedding` is the sum of the weights of the trained model and the original LLaMA,
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so as to ensure that developers with LLaMA original model accessibility can convert the model released by this hub into a usable one.
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First, you can revert the model weights by [this script](https://github.com/Neutralzz/BiLLa/blob/main/embedding_convert.py):
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```shell
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python3 embedding_convert.py \
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print(outputs)
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```
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-
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```
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Human: [Your question]
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Assistant:
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```
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The weight of `word embedding` is the sum of the weights of the trained model and the original LLaMA,
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so as to ensure that developers with LLaMA original model accessibility can convert the model released by this hub into a usable one.
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## Usage
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First, you can revert the model weights by [this script](https://github.com/Neutralzz/BiLLa/blob/main/embedding_convert.py):
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```shell
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python3 embedding_convert.py \
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print(outputs)
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```
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### Input Format
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Different from [BiLLa-7B-LLM](https://huggingface.co/Neutralzz/BiLLa-7B-LLM), the model input of `BiLLa-7B-SFT` should be formatted as follows:
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```
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Human: [Your question]
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Assistant:
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```
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Note that <b>a space</b> is following the `Assistant:`
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