A fast inference library for running LLMs locally on modern consumer-class GPUs

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

The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens.

Scaling Diffusion Transformers with Mixture of Experts

DALL·E Mini - Generate images from a text prompt

tiny vision language model

Fast and memory-efficient exact attention

ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model

Implementation of a Light Recurrent Unit in Pytorch

The full minitorch student suite.

Implementation of a framework for Gamengen in Pytorch

Datasets, Transforms and Models specific to Computer Vision

Coding a Multimodal (Vision) Language Model from scratch in PyTorch with full explanation: https://www.youtube.com/watch?v=vAmKB7iPkWw

Distributed Training Over-The-Internet

Collection of AWESOME vision-language models for vision tasks

image captioninggg🐳

Flux diffusion model implementation using quantized fp8 matmul & remaining layers use faster half precision accumulate, which is ~2x faster on consumer devices.

MLX-Embeddings is the best package for running Vision and Language Embedding models locally on your Mac using MLX.

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑‍🔬

💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows

Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning

A MLX port of FLUX based on the Huggingface Diffusers implementation.

Combining ViT and GPT-2 for image captioning. Trained on MS-COCO. The model was implemented mostly from scratch.

Jax like function transformation engine but micro, microjax

Pytorch implementation of the xLSTM model by Beck et al. (2024)

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…

Generate accurate transcripts using Apple's MLX framework

Diffusion Feedback Helps CLIP See Better

Official inference repo for FLUX.1 models

the scott CPU from "But How Do It Know?" by J. Clark Scott