Pretrained Models
Showing 9 of 9 projects
A model-definition framework for state-of-the-art machine learning models across text, vision, audio, and multimodal tasks.
A model-definition framework for state-of-the-art machine learning models across text, vision, audio, and multimodal tasks.
A comprehensive collection of PyTorch image models, layers, utilities, and training scripts for computer vision research and applications.
Industrial-strength Natural Language Processing library for Python, featuring pretrained pipelines for 70+ languages and production-ready training.
A PyTorch library providing 12+ semantic segmentation model architectures with 800+ pretrained convolutional and transformer-based encoders.
An open-source Python toolkit for speaker diarization with state-of-the-art pretrained models and pipelines.
Automatic and interactive image colorization using deep neural networks, with PyTorch models for ECCV 2016 and SIGGRAPH 2017 papers.
TensorFlow implementation of YOLO for real-time object detection using pretrained YOLO_small, YOLO_tiny, and YOLO_face models.
A BERT language model pre-trained on a large corpus of scientific papers for natural language processing tasks in scientific domains.
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