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---
license: other
inference: false
---
# WizardLM: An Instruction-following LLM Using Evol-Instruct
These files are the result of merging the [delta weights](https://huggingface.co/victor123/WizardLM) with the original Llama7B model.
The code for merging is provided in the [WizardLM official Github repo](https://github.com/nlpxucan/WizardLM).
## WizardLM-7B GGML
This repo contains GGML files for for CPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp).
## Provided files
| Name | Quant method | Bits | Size | RAM required | Use case |
| ---- | ---- | ---- | ---- | ---- | ----- |
`WizardLM-7B.GGML.q4_0.bin` | q4_0 | 4bit | 4.0GB | 6GB | Superseded and not recommended |
`WizardLM-7B.GGML.q4_2.bin` | q4_2 | 4bit | 4.0GB | 6GB | Best compromise between resources, speed and quality |
`WizardLM-7B.GGML.q4_3.bin` | q4_3 | 4bit | 4.8GB | 7GB | Maximum quality, high RAM requirements and slow inference |
* The q4_0 file is provided for compatibility with older versions of llama.cpp. It has been superseded and is no longer recommended.
* The q4_2 file offers the best combination of performance and quality.
* The q4_3 file offers the highest quality, at the cost of increased RAM usage and slower inference speed.
# Original model info
Overview of Evol-Instruct
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.
![info](https://github.com/nlpxucan/WizardLM/raw/main/imgs/git_running.png) |