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README.md
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---
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license: other
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---
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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 13B model produced at Berkeley. It is the result of combining the diffs from https://huggingface.co/young-geng/koala with the original Llama 13B 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) and then converted to GGML for use with [llama.cpp](https://github.com/ggerganov/llama.cpp).
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## Other Koala repos
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I have also made these other Koala models available:
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* [Unquantized 13B model in HF format](https://huggingface.co/TheBloke/koala-13B-HF)
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* [GPTQ quantized 4bit 7B model in `pt` and `safetensors` formats](https://huggingface.co/TheBloke/koala-7B-4bit-128g)
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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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## How to run in `llama.cpp`
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I use the following command line; adjust for your tastes and needs:
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```
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./main -t 18 -m koala-13B-4bit-128g.GGML.bin --color -c 2048 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "BEGINNING OF CONVERSATION:
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USER: <PROMPT GOES HERE>
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GPT:"
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```
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Change `-t 18` to the number of physical CPU cores you have. For example if your system has 8 cores, 16 threads, use `-t 8`.
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You will require 16GB or more RAM to run this model without swapping.
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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-13B-HF](https://huggingface.co/TheBloke/koala-13B-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/TheBloke/llama-13b
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mkdir koala_diffs && cd koala_diffs && wget https://huggingface.co/young-geng/koala/resolve/main/koala_13b_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-13b \
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--output_file=/content/llama-13b-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-13b-LM' \
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--load_target_checkpoint='params::/content/koala_diffs/koala_13b_diff_v2' \
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--output_file=/content/koala_13b.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=13b \
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--output_dir=/content/koala-13B-HF \
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--load_checkpoint='params::/content/koala_13b.diff.weights' \
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--tokenizer_path=/content/llama-13b/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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