OpenNMT/CTranslate2
Fast inference engine for Transformer models
A Flexible Framework for Experiencing Heterogeneous LLM Inference/Fine-tune Optimizations
Fast inference engine for Transformer models
Ongoing research training transformer models at scale
A unified library of SOTA model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
A Next-Generation Training Engine Built for Ultra-Large MoE Models
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
State-of-the-Art Embeddings, Retrieval, and Reranking
1 capture since 2026-05-25