Pretrained Models
Showing 19 of 19 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.
An all-in-one framework for training state-of-the-art computer vision models, covering pretraining, fine-tuning, and distillation.
A curated collection of open-source computer vision pre-trained models across TensorFlow, Keras, PyTorch, Caffe, and MXNet frameworks.
A pretrained modeling library for Keras 3 offering simple, flexible, and fast access to models for text, image, and audio tasks.
Pre-trained BERT models fine-tuned on clinical text from MIMIC for medical natural language processing tasks.
A BERT-based foundation model pretrained on large-scale scRNA-seq data for automated cell type annotation in single-cell analysis.
A large-scale image dataset for self-supervised pretraining without humans, designed to reduce privacy concerns.
A collection of pretrained deep learning models (StyleGAN2, GPT2, VGG, ResNet) for the Jax/Flax ecosystem.
A TensorFlow implementation of the Mnemonic Descent Method for end-to-end face alignment.
Flax implementations and pretrained checkpoints for ResNet, Wide ResNet, ResNeXt, ResNet-D, and ResNeSt in JAX.
A Python package providing popular computer vision model architectures built with Equinox for JAX.
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