Derived from LLaMA2; Outperforming various 3B competitors.
Supported Languages
en (English), zh (Chinese)
Training Details
Methodology:
Fine-tuned from an adapted version of LLaMA2-7B following "Towards the Law of Capacity Gap in Distilling Language Models". Better data mixture; use of NEFTune; use of DPO.
Input Output
Accepted Modalities:
text
Performance Tips:
Use multi-turn conversation by continuously appending questions to the `conv`. Set `torch_dtype` to `torch.float16` for better performance on compatible hardware.
Release Notes
Version:
MiniChat-1.5-3B
Notes:
Better data mixture; use of NEFTune; use of DPO. Derived from LLaMA2.
Note: green Score (e.g. "73.2") means that the model is better than GeneZC/MiniChat-1.5-3B.
Rank the MiniChat 1.5 3B Capabilities
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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation
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