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A feature-rich command-line audio/video downloader
🤗 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.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
We write your reusable computer vision tools. 💜
Streamlit — A faster way to build and share data apps.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
TensorFlow code and pre-trained models for BERT
An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
PyTorch Tutorial for Deep Learning Researchers
A Pocket-Sized MLLM for Ultra-Efficient Image and Video Understanding on Your Phone
Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
Toolkit for linearizing PDFs for LLM datasets/training
State-of-the-Art Embeddings, Retrieval, and Reranking
Janus-Series: Unified Multimodal Understanding and Generation Models
Computer Vision Annotation Tool (CVAT) is a leading platform for building high-quality visual datasets for vision AI. It offers open-source, cloud, and enterprise products, as well as labeling serv…
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Powerline is a statusline plugin for vim, and provides statuslines and prompts for several other applications, including zsh, bash, tmux, IPython, Awesome and Qtile.
[CVPR 2025 Best Paper Award] VGGT: Visual Geometry Grounded Transformer
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
Node-based Visual Programming Toolbox
A collaboration friendly studio for NeRFs
Cross-platform lib for process and system monitoring in Python