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--- |
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license: other |
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inference: false |
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--- |
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# gpt4-x-vicuna-13B-GGML |
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These files are GGML format model files of [NousResearch's gpt4-x-vicuna-13b](https://huggingface.co/NousResearch/gpt4-x-vicuna-13b). |
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GGML files are for CPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp). |
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## Repositories available |
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* [4bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/gpt4-x-vicuna-13B-GPTQ). |
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* [4bit and 5bit GGML models for CPU inference](https://huggingface.co/TheBloke/gpt4-x-vicuna-13B-GGML). |
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* [float16 HF model for unquantised and 8bit GPU inference](https://huggingface.co/TheBloke/gpt4-x-vicuna-13B-HF). |
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## REQUIRES LATEST LLAMA.CPP (May 12th 2023 - commit b9fd7ee)! |
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llama.cpp recently made a breaking change to its quantisation methods. |
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I have re-quantised the GGML files in this repo. Therefore you will require llama.cpp compiled on May 12th or later (commit `b9fd7ee` or later) to use them. |
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The previous files, which will still work in older versions of llama.cpp, can be found in branch `previous_llama`. |
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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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`gpt4-x-vicuna-13B.ggml.q4_0.bin` | q4_0 | 4bit | 8.14GB | 10GB | 4-bit. | |
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`gpt4-x-vicuna-13B.ggml.q5_0.bin` | q5_0 | 5bit | 8.95GB | 11GB | 5-bit. Higher accuracy, higher resource usage and slower inference. | |
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`gpt4-x-vicuna-13B.ggml.q5_1.bin` | q5_1 | 5bit | 9.76GB | 12GB | 5-bit. Even higher accuracy, higher resource usage and slower inference. | |
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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 gpt4-x-vicuna-13B.ggml.q4_2.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 will not support the newly updated llama.cpp quantisation methods. |
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**Thireus** has written a [great guide on how to update it to the latest llama.cpp code](https://huggingface.co/TheBloke/wizardLM-7B-GGML/discussions/5) so that you can get support for the new llama.cpp quantisation methods sooner. |
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# Original model card |
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As a base model used https://huggingface.co/eachadea/vicuna-13b-1.1 |
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Finetuned on Teknium's GPTeacher dataset, unreleased Roleplay v2 dataset, GPT-4-LLM dataset, and Nous Research Instruct Dataset |
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Approx 180k instructions, all from GPT-4, all cleaned of any OpenAI censorship/"As an AI Language Model" etc. |
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Base model still has OpenAI censorship. Soon, a new version will be released with cleaned vicuna from https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltere |
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Trained on 8 A100-80GB GPUs for 5 epochs following Alpaca deepspeed training code. |
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Nous Research Instruct Dataset will be released soon. |
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GPTeacher, Roleplay v2 by https://huggingface.co/teknium |
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Wizard LM by https://github.com/nlpxucan |
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Nous Research Instruct Dataset by https://huggingface.co/karan4d and https://huggingface.co/huemin |
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Compute provided by our project sponsor https://redmond.ai/ |
