WizardLM: An Instruction-following LLM Using Evol-Instruct
These files are the result of merging the delta weights with the original Llama7B model.
The code for merging is provided in the WizardLM official Github repo.
The original WizardLM deltas are in float32, and this results in producing an HF repo that is also float32, and is much larger than a normal 7B Llama model.
Therefore for this repo I converted the merged model to float16, to produce a standard size 7B model.
This was achieved by running model = model.half() prior to saving.
WizardLM-7B HF
This repo contains the full unquantised model files in HF format for GPU inference and as a base for quantisation/conversion.
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Thanks, and how to contribute.
Thanks to the chirper.ai team!
I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training.
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Original model info
Full details in the model's Github page
WizardLM official Github repo.
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.
Although on our complexity-balanced test set, WizardLM-7B outperforms ChatGPT in the high-complexity instructions, it still lag behind ChatGPT on the entire test set, and we also consider WizardLM to still be in a baby state. This repository will continue to improve WizardLM, train on larger scales, add more training data, and innovate more advanced large-model training methods.
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