🤗 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.
- nlp
- natural-language-processing
- pytorch
- pytorch-transformers
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🤗 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.
The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface. The fastest local inference engine in the world.
1 min voice data can also be used to train a good TTS model! (few shot voice cloning)
Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Making large AI models cheaper, faster and more accessible
VoxCPM2: Tokenizer-Free TTS for Multilingual Speech Generation, Creative Voice Design, and True-to-Life Cloning
A generative speech model for daily dialogue.
Easily train a good VC model with voice data <= 10 mins!
Instant voice cloning by MIT and MyShell. Audio foundation model.
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
Official Code for DragGAN (SIGGRAPH 2023)
Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text in a single forward pass, in 100+ languages, with a router that picks the right checkpoint per request.
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
Let us control diffusion models!
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Code and documentation to train Stanford's Alpaca models, and generate the data.
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
Generative Models by Stability AI
Official inference repo for FLUX.1 models
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
Multi-lingual large voice generation model, providing inference, training and deployment full-stack ability.
Universal LLM Deployment Engine with ML Compilation