---
license: other
library_name: transformers
pipeline_tag: text-generation
datasets: 
- RyokoAI/ShareGPT52K
- Hello-SimpleAI/HC3
tags:
- koala
- ShareGPT
- llama
- gptq
---

# Koala: A Dialogue Model for Academic Research
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.

This version has then been converted to HF format.

## My Koala repos
I have the following Koala model repositories available:

**13B models:**
* [Unquantized 13B model in HF format](https://huggingface.co/TheBloke/koala-13B-HF)
* [GPTQ quantized 4bit 13B model in `pt` and `safetensors` formats](https://huggingface.co/TheBloke/koala-13B-GPTQ-4bit-128g)
* [GPTQ quantized 4bit 13B model in GGML format for `llama.cpp`](https://huggingface.co/TheBloke/koala-13B-GPTQ-4bit-128g-GGML)
  
**7B models:**
* [Unquantized 7B model in HF format](https://huggingface.co/TheBloke/koala-7B-HF)
* [Unquantized 7B model in GGML format for llama.cpp](https://huggingface.co/TheBloke/koala-7b-ggml-unquantized)
* [GPTQ quantized 4bit 7B model in `pt` and `safetensors` formats](https://huggingface.co/TheBloke/koala-7B-GPTQ-4bit-128g)
* [GPTQ quantized 4bit 7B model in GGML format for `llama.cpp`](https://huggingface.co/TheBloke/koala-7B-GPTQ-4bit-128g-GGML)

## How the Koala delta weights were merged

The Koala delta weights were merged using the following commands:
```
git clone https://github.com/young-geng/EasyLM

git clone https://huggingface.co/nyanko7/LLaMA-7B

git clone https://huggingface.co/young-geng/koala koala_diffs

cd EasyLM

PYTHON_PATH="${PWD}:$PYTHONPATH" python \
-m EasyLM.models.llama.convert_torch_to_easylm \
--checkpoint_dir=/content/LLaMA-7B \
--output_file=/content/llama-7B-LM \
--streaming=True

PYTHON_PATH="${PWD}:$PYTHONPATH" python \
-m EasyLM.scripts.diff_checkpoint --recover_diff=True \
--load_base_checkpoint='params::/content/llama-7B-LM' \
--load_target_checkpoint='params::/content/koala_diffs/koala_7b_diff_v2' \
--output_file=/content/koala_7b.diff.weights \
--streaming=True

PYTHON_PATH="${PWD}:$PYTHONPATH" python \
-m EasyLM.models.llama.convert_easylm_to_hf --model_size=7b \
--output_dir=/content/koala-7B-HF \
--load_checkpoint='params::/content/koala_7b.diff.weights' \
--tokenizer_path=/content/LLaMA-7B/tokenizer.model
```

Check out the following links to learn more about the Berkeley Koala model.
* [Blog post](https://bair.berkeley.edu/blog/2023/04/03/koala/)
* [Online demo](https://koala.lmsys.org/)
* [EasyLM: training and serving framework on GitHub](https://github.com/young-geng/EasyLM)
* [Documentation for running Koala locally](https://github.com/young-geng/EasyLM/blob/main/docs/koala.md)

## License
The model weights are intended for academic research only, subject to the
[model License of LLaMA](https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md),
[Terms of Use of the data generated by OpenAI](https://openai.com/policies/terms-of-use),
and [Privacy Practices of ShareGPT](https://chrome.google.com/webstore/detail/sharegpt-share-your-chatg/daiacboceoaocpibfodeljbdfacokfjb).
Any other usage of the model weights, including but not limited to commercial usage, is strictly prohibited.