This is an English automatic speech recognition model developed by Applied Brain Research (ABR) based on the state space model (SSM). It has approximately 19 million parameters and can efficiently and accurately transcribe English speech into text. The model performs excellently on multiple benchmark datasets, with an average word error rate of only 10.61%. It supports real-time speech recognition and can run on low-cost hardware.

Audio ProcessingTransformersEnglish

FairyR1-32B is an efficient large language model developed by Peking University DS-LAB, based on DeepSeek-R1-Distill-Qwen-32B. It achieves a balance between high performance and low-cost inference through an innovative 'distillation-fusion' process.

Natural Language ProcessingTransformersEnglish

Action Chunking Transformer (ACT) model trained on the AdamLucek/koch_block dataset, suitable for Koch v1.1 low-cost robots

Computer VisionSafetensors

An efficient text-to-image generation model based on Würstchen architecture, achieving fast inference and low-cost training through a 42x compression factor

MultimodalDiffusers