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[English Version]
The main features of da-southampton/redgpt are: Instruction Datasets.
Projects with overlapping indexed features include: cluebenchmark/pclue. freedomintelligence/huatuo-26m — The Largest-scale Chinese Medical QA Dataset： with 26,000,000 question answer pairs. instruction-tuning-with-gpt-4/gpt-4-llm — This project is an instruction tuning framework and synthetic data generator that uses high-capacity teacher models to… lianjiatech/belle — BELLE is a specialized implementation of Chinese conversational large language models, encompassing a full instruction… phoebussi/alpaca-cot — We unified the interfaces of instruction-tuning data (e.g., CoT data), multiple LLMs and parameter-efficient methods… plexpt/chatgpt-corpus — This project provides a comprehensive Chinese language corpus designed to support the training and fine-tuning of…
The Largest-scale Chinese Medical QA Dataset： with 26,000,000 question answer pairs.
This project is an instruction tuning framework and synthetic data generator that uses high-capacity teacher models to produce instruction-following pairs for training smaller student models. It provides datasets and tools for supervised instruction tuning and reinforcement learning from human feedback. The framework specializes in cross-lingual tuning, offering high-quality instruction-following examples in English and Chinese to improve model generalization across different scripts. It includes a reward modeling tool for creating preference datasets and comparative ratings used to train rew
BELLE is a specialized implementation of Chinese conversational large language models, encompassing a full instruction tuning framework. It provides a pipeline for training, evaluating, and deploying models optimized for natural language understanding and dialogue tasks in the Chinese language. The project is distinguished by its integrated approach to model refinement, combining the curation of multi-million entry instruction datasets with a distributed training pipeline. This pipeline supports both full fine-tuning and low-rank adaptation to optimize conversational performance. The system
