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WizardLM

by Microsoft and Peking University

Empowering Large Pre-Trained Language Models to Follow Complex Instructions
Text
Full
https://github.com/nlpxucan/WizardLM
LLaMA-7B
Evol-Instruct (synthetic)
Llama 2 Community License Agreement
Microsoft, a major tech company, and Peking University, a Chinese university.
https://github.com/nlpxucan
April 2023
Availability
Base Model Data
Based on LLaMA, which is claimed to be public but nowhere exactly documented.
https://github.com/opening-up-chatgpt/opening-up-chatgpt.github.io/blob/main/projects/llama-2-chat.yaml
End User Model Data
The Evol-Instruct dataset contains 70k instruction-following sequences generated from Evol-Instruct
https://github.com/nlpxucan/WizardLM/tree/main/WizardLM#training-data
Base Model Weights
Based on LLaMA weights, which are not openly available though a leaked versions is in wide circulation.
End User Model Weights
Model weights offered as a delta to LLaMA
https://huggingface.co/WizardLM/WizardLM-7B-V1.0/tree/main
Training Code
Reasonably useful source code repository but as this is based on Llama, the underlying source is not available.
https://github.com/nlpxucan/WizardLM/tree/main/WizardLM
Documentation
Code Documentation
Code is comprehensively documented and contains demos.
https://github.com/nlpxucan/WizardLM/tree/main/WizardLM
Hardware Architecture
Architecture described in preprint and partly accessible in code repository
https://arxiv.org/abs/2304.12244
Preprint
Preprint describes method for creating large amounts of LLM-based synthetic RLHF data and fine-tuning WizardLM based on it
https://arxiv.org/abs/2304.12244
Paper
Paper published in ICLR.
https://proceedings.iclr.cc/paper_files/paper/2024/hash/82eec786fdfbbfa53450c5feb7d1ac92-Abstract-Conference.html
Modelcard
Model card is available, however contains links to pages talking about the model architecture, training, fine-tuning, and evaluation rather than containing them itself.
https://huggingface.co/WizardLM/WizardLM-7B-V1.0
Datasheet
Dataset card is available, but provides no information about data collection and curation. The preprint outlines data collection (based on a 52K instruction dataset from Alpaca) and curation at a high level.
https://huggingface.co/datasets/WizardLM/WizardLM_evol_instruct_V2_196k
Access
Licenses
Restricted for academic research purposes only. Code and Model diff release under CC-BY-NC-4.0, software code under Apache 2.0
https://github.com/nlpxucan/WizardLM/blob/main/WizardLM/MODEL_DIFF_LICENSE
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