A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

An open-source RAG-based tool for chatting with your documents.

Hands-on tutorials on fine-tuning various LLMs using different fine-tuning techniques

AirLLM 70B inference with single 4GB GPU

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's …

DSPy: The framework for programming—not prompting—foundation models

This includes the original implementation of SELF-RAG: Learning to Retrieve, Generate and Critique through self-reflection by Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi.

Boolformer, best fit for noisy data.

1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.

Configurable Generation of Schemas and Knowledge Graphs at Your Fingertips

QLoRA: Efficient Finetuning of Quantized LLMs

The simplest, fastest repository for training/finetuning medium-sized GPTs.

The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo

Vulnerability Management Platform

Implementation of Google's PaLM models

Dashboard generator using OpenAI's GPT3

Free and open source log management

This repository contains demos I made with the Transformers library by HuggingFace.

Algorithms for explaining machine learning models