hiyouga/LlamaFactory
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
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Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
Multimodal RL training framework for diffusion & omni models
Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation, dataset management, MCP, and more.
Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
Distilabel is a framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable pipelines based on verified research papers.
A scalable, agentic-first, and HuggingFace-native RL framework for research (9k lines).
An Efficient and User-Friendly Scaling Library for Reinforcement Learning with Large Language Models
A native Mac App for LLM fine-tuning on Apple Silicon — fully on-device, fully open source.
Halo is an open-source framework built by White Circle for training large language and multimodal models
Xtreme1 is an all-in-one data labeling and annotation platform for multimodal data training and supports 3D LiDAR point cloud, image, and LLM.
An Asynchronous Reinforcement Learning Engine for Omni-Modal Post-Training at Scale
Train Large Language Models on MLX.
RewardBench: the first evaluation tool for reward models.
The open source research environment for AI researchers to seamlessly train, evaluate, and scale models from local hardware to GPU clusters.
That's all 14 repositories in this period.