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license: other |
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inference: false |
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--- |
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# WizardLM: An Instruction-following LLM Using Evol-Instruct |
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These files are the result of merging the [delta weights](https://huggingface.co/victor123/WizardLM) with the original Llama7B model. |
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The code for merging is provided in the [WizardLM official Github repo](https://github.com/nlpxucan/WizardLM). |
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## WizardLM-7B GGML |
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This repo contains GGML files for for CPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp). |
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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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`WizardLM-7B.GGML.q4_0.bin` | q4_0 | 4bit | 4.0GB | 6GB | Superseded and not recommended | |
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`WizardLM-7B.GGML.q4_2.bin` | q4_2 | 4bit | 4.0GB | 6GB | Best compromise between resources, speed and quality | |
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`WizardLM-7B.GGML.q4_3.bin` | q4_3 | 4bit | 4.8GB | 7GB | Maximum quality, high RAM requirements and slow inference | |
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* The q4_0 file is provided for compatibility with older versions of llama.cpp. It has been superseded and is no longer recommended. |
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* The q4_2 file offers the best combination of performance and quality. |
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* The q4_3 file offers the highest quality, at the cost of increased RAM usage and slower inference speed. |
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# Original model info |
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Overview of Evol-Instruct |
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Evol-Instruct is a novel method using LLMs instead of humans to automatically mass-produce open-domain instructions of various difficulty levels and skills range, to improve the performance of LLMs. |
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