Amazon SageMaker Local Mode Examples

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Notebooks using the Hugging Face libraries 🤗

Stable Diffusion web UI

An Engine-Agnostic Deep Learning Framework in Java

Inference code for Llama models

Standardized Serverless ML Inference Platform on Kubernetes

Tracking Any Point (TAP)

MLOps workshop with Amazon SageMaker

Benchmarks of approximate nearest neighbor libraries in Python

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…

NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.

Reference implementations of several LangChain agents as Streamlit apps

Opiniated RAG for integrating GenAI in your apps 🧠 Focus on your product rather than the RAG. Easy integration in existing products with customisation! Any LLM: GPT4, Groq, Llama. Any Vectorstore: …

The Open Source Feature Store for AI/ML

New ways of breaking app-integrated LLMs

AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker

Example code for AWS Neuron SDK developers building inference and training applications

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama mode…

PyTorch extensions for high performance and large scale training.

Human preference data for "Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback"

Trained models & code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using ⚡ Pytorch Lightning and 🤗 Transformers. For access to our API, please email us at contact@unita…

Go ahead and axolotl questions

A framework for few-shot evaluation of language models.

[CCS'24] A dataset consists of 15,140 ChatGPT prompts from Reddit, Discord, websites, and open-source datasets (including 1,405 jailbreak prompts).

Foundation Model Evaluations Library