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--- |
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license: other |
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--- |
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# Koala: A Dialogue Model for Academic Research |
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This repo contains the weights of the Koala 7B model produced at Berkeley. It is the result of combining the diffs from https://huggingface.co/young-geng/koala with the original Llama 7B model. |
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This version has then been quantized to 4-bit using [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa). |
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## Other Koala repos |
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I have also made these other Koala models available: |
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* [GPTQ quantized 4bit 13B model in `pt` and `safetensors` formats](https://huggingface.co/TheBloke/koala-13B-GPTQ-4bit-128g) |
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* [Unquantized 13B model in HF format](https://huggingface.co/TheBloke/koala-13B-HF) |
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* [Unquantized 7B model in HF format](https://huggingface.co/TheBloke/koala-7B-HF) |
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* [Unquantized 7B model in GGML format for llama.cpp](https://huggingface.co/TheBloke/koala-7b-ggml-unquantized) |
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## Quantization method |
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This GPTQ model was quantized using [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa) with the following commands: |
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``` |
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python3 llama.py /content/koala-7B-HF c4 --wbits 4 --true-sequential --act-order --groupsize 128 --save /content/koala-7B-4bit-128g.pt |
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python3 llama.py /content/koala-7B-HF c4 --wbits 4 --true-sequential --act-order --groupsize 128 --save_safetensors /content/koala-7B-4bit-128g.safetensors |
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``` |
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I used the latest Triton branch of `GPTQ-for-LLaMa` but they can also be loaded with the CUDA branch. |
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## Provided files |
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I have provided both a `pt` and `safetensors` file. Either should work. |
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If both are present in the model directory for text-generation-webui I am not sure which it chooses, so you may want to place only one in the models folder. |
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The `olderFormat` file was created with the aim of then converting it to GGML for use with [llama.cpp](https://github.com/ggerganov/llama.cpp). At present this file does not work. |
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## How to run with `text-generation-webui` |
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GPTQ model files provided will not load as-is with [oobaboogas text-generation-webui](https://github.com/oobabooga/text-generation-webui). |
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These model files require the latest version of the GPTQ code. |
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Here are the commands I used to clone the Triton branch of GPTQ-for-LLaMa, clone text-generation-webui, and install GPTQ into the UI: |
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``` |
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git clone https://github.com/qwopqwop200/GPTQ-for-LLaMa |
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git clone https://github.com/oobabooga/text-generation-webui |
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mkdir -p text-generation-webui/repositories |
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ln -s GPTQ-for-LLaMa text-generation-webui/repositories/GPTQ-for-LLaMa |
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``` |
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Then install this model into `text-generation-webui/models` and launch the UI as follows: |
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``` |
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cd text-generation-webui |
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python server.py --model koala-7B-4bit-128g --wbits 4 --groupsize 128 --model_type Llama # add any other command line args you want |
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``` |
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The above commands assume you have installed all dependencies for GPTQ-for-LLaMa and text-generation-webui. Please see their respective repositories for further information. |
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If you cannot use the Triton branch of GPTQ for any reason, you can alternatively use the CUDA branch instead: |
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``` |
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git clone https://github.com/qwopqwop200/GPTQ-for-LLaMa -b cuda |
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cd GPTQ-for-LLaMa |
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python setup_cuda.py install |
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``` |
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Then link that into `text-generation-webui/repositories` as described above. |
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## How the Koala delta weights were merged |
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The Koala delta weights were originally merged using the following commands, producing [koala-7B-HF](https://huggingface.co/TheBloke/koala-7B-HF): |
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``` |
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git clone https://github.com/young-geng/EasyLM |
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git clone https://huggingface.co/nyanko7/LLaMA-7B |
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mkdir koala_diffs && cd koala_diffs && wget https://huggingface.co/young-geng/koala/resolve/main/koala_7b_diff_v2 |
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cd EasyLM |
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PYTHON_PATH="${PWD}:$PYTHONPATH" python \ |
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-m EasyLM.models.llama.convert_torch_to_easylm \ |
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--checkpoint_dir=/content/LLaMA-7B \ |
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--output_file=/content/llama-7B-LM \ |
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--streaming=True |
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PYTHON_PATH="${PWD}:$PYTHONPATH" python \ |
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-m EasyLM.scripts.diff_checkpoint --recover_diff=True \ |
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--load_base_checkpoint='params::/content/llama-7B-LM' \ |
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--load_target_checkpoint='params::/content/koala_diffs/koala_7b_diff_v2' \ |
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--output_file=/content/koala_7b.diff.weights \ |
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--streaming=True |
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PYTHON_PATH="${PWD}:$PYTHONPATH" python \ |
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-m EasyLM.models.llama.convert_easylm_to_hf --model_size=7b \ |
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--output_dir=/content/koala-7B-HF \ |
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--load_checkpoint='params::/content/koala_7b.diff.weights' \ |
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--tokenizer_path=/content/LLaMA-7B/tokenizer.model |
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``` |
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## Further info |
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Check out the following links to learn more about the Berkeley Koala model. |
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* [Blog post](https://bair.berkeley.edu/blog/2023/04/03/koala/) |
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* [Online demo](https://koala.lmsys.org/) |
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* [EasyLM: training and serving framework on GitHub](https://github.com/young-geng/EasyLM) |
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* [Documentation for running Koala locally](https://github.com/young-geng/EasyLM/blob/main/docs/koala.md) |
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## License |
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The model weights are intended for academic research only, subject to the |
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[model License of LLaMA](https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md), |
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[Terms of Use of the data generated by OpenAI](https://openai.com/policies/terms-of-use), |
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and [Privacy Practices of ShareGPT](https://chrome.google.com/webstore/detail/sharegpt-share-your-chatg/daiacboceoaocpibfodeljbdfacokfjb). |
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Any other usage of the model weights, including but not limited to commercial usage, is strictly prohibited. |
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