Initial GGML model commit
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README.md
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---
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inference: false
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license: other
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---
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# Tim Dettmers' Guanaco 7B GGML
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These files are GGML format model files for [Tim Dettmers' Guanaco 7B](https://huggingface.co/timdettmers/guanaco-7b).
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GGML files are for CPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp) and libraries and UIs which support this format, such as:
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* [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
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* [KoboldCpp](https://github.com/LostRuins/koboldcpp)
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* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python)
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* [ctransformers](https://github.com/marella/ctransformers)
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## Other repositories available
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* [4-bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/guanaco-7B-GPTQ)
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* [4-bit, 5-bit, and 8-bit GGML models for CPU+GPU inference](https://huggingface.co/TheBloke/guanaco-7B-GGML)
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* [Original unquantised fp16 model in HF format](https://huggingface.co/timdettmers/guanaco-7b)
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## THE FILES IN MAIN BRANCH REQUIRES LATEST LLAMA.CPP (May 19th 2023 - commit 2d5db48)!
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llama.cpp recently made another breaking change to its quantisation methods - https://github.com/ggerganov/llama.cpp/pull/1508
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I have quantised the GGML files in this repo with the latest version. Therefore you will require llama.cpp compiled on May 19th or later (commit `2d5db48` or later) to use them.
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## Provided files
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| Name | Quant method | Bits | Size | RAM required | Use case |
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| ---- | ---- | ---- | ---- | ---- | ----- |
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| guanaco-7B.ggmlv3.q4_0.bin | q4_0 | 4 | 3.79 GB | 6.29 GB | 4-bit. |
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| guanaco-7B.ggmlv3.q4_1.bin | q4_1 | 4 | 4.21 GB | 6.71 GB | 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models. |
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| guanaco-7B.ggmlv3.q5_0.bin | q5_0 | 5 | 4.63 GB | 7.13 GB | 5-bit. Higher accuracy, higher resource usage and slower inference. |
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| guanaco-7B.ggmlv3.q5_1.bin | q5_1 | 5 | 5.06 GB | 7.56 GB | 5-bit. Even higher accuracy, resource usage and slower inference. |
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| guanaco-7B.ggmlv3.q8_0.bin | q8_0 | 8 | 7.16 GB | 9.66 GB | 8-bit. Almost indistinguishable from float16. Huge resource use and slow. Not recommended for normal use. |
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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 12 -m guanaco-7B.v3.q5_0.bin --color -c 2048 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "Below is an instruction that describes a task. Write a response that appropriately completes the request.
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### Instruction:
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Write a story about llamas
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### Response:"
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```
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Change `-t 12` 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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If you want to have a chat-style conversation, replace the `-p <PROMPT>` argument with `-i -ins`
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## How to run in `text-generation-webui`
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Further instructions here: [text-generation-webui/docs/llama.cpp-models.md](https://github.com/oobabooga/text-generation-webui/blob/main/docs/llama.cpp-models.md).
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Note: at this time text-generation-webui may not support the new May 19th llama.cpp quantisation methods for q4_0, q4_1 and q8_0 files.
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# Original model card: Tim Dettmers' Guanaco 7B
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