🦜🔗 Build context-aware reasoning applications

A latent text-to-image diffusion model

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

🔊 Text-Prompted Generative Audio Model

Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable…

Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

Code for Machine Learning for Algorithmic Trading, 2nd edition.

A multi-voice TTS system trained with an emphasis on quality

Foundational Models for State-of-the-Art Speech and Text Translation

LAVIS - A One-stop Library for Language-Vision Intelligence

QLoRA: Efficient Finetuning of Quantized LLMs

A series of large language models trained from scratch by developers @01-ai

A unified framework for 3D content generation.

A Bulletproof Way to Generate Structured JSON from Language Models

Segment Anything in High Quality [NeurIPS 2023]

A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain

Jupyter Notebooks to help you get hands-on with Pinecone vector databases

EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything

[ICLR24] Official PyTorch Implementation of Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors

Tracking Any Point (TAP)

🚀 BARK INFINITY GUI CMD 🎶 Powered Up Bark Text-prompted Generative Audio Model

Learn to build and deploy AI apps.

Official PyTorch implementation of "EdgeSAM: Prompt-In-the-Loop Distillation for On-Device Deployment of SAM"

[NeurIPS 22] [AAAI 24] Recurrent Transformer-based long-context architecture.

🐟 Code and models for the NeurIPS 2023 paper "Generating Images with Multimodal Language Models".