thanks to TheBloke ❤

README.md

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+---
+license: other
+library_name: transformers
+pipeline_tag: text-generation
+datasets: 
+- RyokoAI/ShareGPT52K
+- Hello-SimpleAI/HC3
+tags:
+- koala
+- ShareGPT
+- llama
+- gptq
+inference: false
+---
+# Koala: A Dialogue Model for Academic Research
+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.
+
+This version has then been quantized to 4-bit using [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa).
+
+## 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)
+
+## Provided files
+
+Three model files are provided. You don't need all three - choose the one that suits your needs best!
+
+Details of the files provided:
+* `koala-13B-4bit-128g.pt`
+  * pt format file, created with the latest [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa) code.
+  * Command to create:
+    * `python3 llama.py koala-13B-HF c4 --wbits 4 --true-sequential --act-order --groupsize 128 --save koala-13B-4bit-128g.pt`
+* `koala-13B-4bit-128g.safetensors`
+  * newer `safetensors` format, with improved file security, created with the latest [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa) code.
+  * Command to create:
+    * `python3 llama.py koala-13B-HF c4 --wbits 4 --true-sequential --act-order --groupsize 128 --save_safetensors koala-13B-4bit-128g.safetensors`
+* `koala-13B-4bit-128g.no-act-order.ooba.pt`
+  * `pt` format file, created with [oobabooga's older CUDA fork of GPTQ-for-LLaMa](https://github.com/oobabooga/GPTQ-for-LLaMa).
+  * This file is included primarily for Windows users, as it can be used without needing to compile the latest GPTQ-for-LLaMa code.
+  * It should hopefully therefore work with one-click-installers on Windows, which include the older GPTQ-for-LLaMa code.
+  * The older GPTQ code does not support all the latest features, so the quality may be fractionally lower.
+  * Command to create:
+    * `python3 llama.py koala-13B-HF c4 --wbits 4 --true-sequential --groupsize 128 --save koala-13B-4bit-128g.no-act-order.ooba.pt`
+
+## How to run in `text-generation-webui`
+
+File `koala-13B-4bit-128g.no-act-order.ooba.pt` can be loaded the same as any other GPTQ file, without requiring any updates to [oobaboogas text-generation-webui](https://github.com/oobabooga/text-generation-webui).
+
+The other two model files were created with the latest GPTQ code, and require that the latest GPTQ-for-LLaMa is used inside the UI.
+
+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:
+```
+git clone https://github.com/qwopqwop200/GPTQ-for-LLaMa
+git clone https://github.com/oobabooga/text-generation-webui
+mkdir -p text-generation-webui/repositories
+ln -s GPTQ-for-LLaMa text-generation-webui/repositories/GPTQ-for-LLaMa
+```
+
+Then install this model into `text-generation-webui/models` and launch the UI as follows:
+```
+cd text-generation-webui
+python server.py --model koala-13B-GPTQ-4bit-128g --wbits 4 --groupsize 128 --model_type Llama # add any other command line args you want
+```
+
+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.
+
+If you are on Windows, or cannot use the Triton branch of GPTQ for any other reason, you can instead use the CUDA branch:
+```
+git clone https://github.com/qwopqwop200/GPTQ-for-LLaMa -b cuda
+cd GPTQ-for-LLaMa
+python setup_cuda.py install
+```
+Then link that into `text-generation-webui/repositories` as described above.
+
+Or just use `koala-13B-4bit-128g.no-act-order.ooba.pt` as mentioned above.
+
+## How the Koala delta weights were merged
+
+The Koala delta weights were originally merged using the following commands, producing [koala-13B-HF](https://huggingface.co/TheBloke/koala-13B-HF):
+```
+git clone https://github.com/young-geng/EasyLM
+
+git clone https://huggingface.co/TheBloke/llama-13b
+
+mkdir koala_diffs && cd koala_diffs && wget https://huggingface.co/young-geng/koala/resolve/main/koala_13b_diff_v2
+
+cd EasyLM
+
+PYTHON_PATH="${PWD}:$PYTHONPATH" python \
+-m EasyLM.models.llama.convert_torch_to_easylm \
+--checkpoint_dir=/content/llama-13b \
+--output_file=/content/llama-13b-LM \
+--streaming=True
+
+PYTHON_PATH="${PWD}:$PYTHONPATH" python \
+-m EasyLM.scripts.diff_checkpoint --recover_diff=True \
+--load_base_checkpoint='params::/content/llama-13b-LM' \
+--load_target_checkpoint='params::/content/koala_diffs/koala_13b_diff_v2' \
+--output_file=/content/koala_13b.diff.weights \
+--streaming=True
+
+PYTHON_PATH="${PWD}:$PYTHONPATH" python \
+-m EasyLM.models.llama.convert_easylm_to_hf --model_size=13b \
+--output_dir=/content/koala-13B-HF \
+--load_checkpoint='params::/content/koala_13b.diff.weights' \
+--tokenizer_path=/content/llama-13b/tokenizer.model
+```
+
+## Further info
+
+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.

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 13824,
+  "max_position_embeddings": 2048,
+  "model_type": "llama",
+  "num_attention_heads": 40,
+  "num_hidden_layers": 40,
+  "pad_token_id": 0,
+  "rms_norm_eps": 1e-06,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.28.0.dev0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 0,
+  "transformers_version": "4.28.0.dev0"
+}

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