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18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
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.
🔊 Text-Prompted Generative Audio Model
A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Instruct-tune LLaMA on consumer hardware
A guidance language for controlling large language models.
StableLM: Stability AI Language Models
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
A multi-voice TTS system trained with an emphasis on quality
High-Resolution Image Synthesis with Latent Diffusion Models
Neural Networks: Zero to Hero
llama3 implementation one matrix multiplication at a time
Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization and Q&A. Supportin…
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
QLoRA: Efficient Finetuning of Quantized LLMs
LAVIS - A One-stop Library for Language-Vision Intelligence
Official inference library for Mistral models
An open source implementation of CLIP.
This repository contains demos I made with the Transformers library by HuggingFace.
PyTorch code and models for the DINOv2 self-supervised learning method.
Using Low-rank adaptation to quickly fine-tune diffusion models.
Taming Transformers for High-Resolution Image Synthesis
Tacotron 2 - PyTorch implementation with faster-than-realtime inference
Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models l…