7 Repos
Techniques for instruction tuning, in-context learning, and continual skill acquisition.
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This project is a comprehensive framework and toolkit for developing, optimizing, and deploying transformer-based models across multimodal, document intelligence, and natural language processing tasks. It provides a unified neural architecture that processes text, vision, audio, and document layout data through a shared set of weights, enabling researchers and developers to build foundational models that align cross-modal representations. The platform distinguishes itself through advanced training and inference strategies designed for large-scale deep learning. It incorporates specialized mec
Neural codec models for zero-shot in-context learning.
Go to T5X ReadTheDocs Documentation Page.
Scalable instruction-finetuning for diverse task performance.
Painter & SegGPT Series: Vision Foundation Models from BAAI
Generalist model for in-context visual learning tasks.
🤗 Model (AgentLM-70B) • 🤗 Dataset (AgentInstruct) • 📃 Paper • 🌐 Project Page
Instruction tuning to enable generalized agent capabilities.
Benchmark and environment for evolving agents across diverse tasks.
Multitask training for zero-shot task generalization.
Harmonizes natural language and code for improved agent generalization.