🦜🔗 Build context-aware reasoning applications

A latent text-to-image diffusion model

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

🔊 Text-Prompted Generative Audio Model

A guidance language for controlling large language models.

Instruct-tune LLaMA on consumer hardware

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

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

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…

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

An open-source, low-code machine learning library in Python

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

Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion

Lab Materials for MIT 6.S191: Introduction to Deep Learning

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

JAX implementation of OpenAI's Whisper model for up to 70x speed-up on TPU.

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

SoTA LLM for converting natural language questions to SQL queries

A high performance implementation of HDBSCAN clustering.

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

SAM with text prompt

Training LLMs with QLoRA + FSDP

Neural question generation using transformers

Compare the performance of different LLM that can be deployed locally on consumer hardware. Run yourself with Colab WebUI.

Generating multiple choice questions from text using Machine Learning.

Implementations in python of methods and programming assignments of course Machine Learning of Coursera by Andrew Ng

Here you can find all the Tutorials for Haystack 📓