Toolkit for creating, sharing and using natural language prompts.

Integrate cutting-edge LLM technology quickly and easily into your apps

An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.

AutoML for clustering models in sklearn.

List of resources for learning about modeling, operating, and using Amazon DynamoDB

OB-UDPST is a client/server utility to do UDP-based IP capacity measurements (see TR-471 for details).

Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"

This repo includes ChatGPT prompt curation to use ChatGPT and other LLM tools better.

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

The code and data for "StructGPT: A general framework for Large Language Model to Reason on Structured Data"

[EMNLP 2022] Unifying and multi-tasking structured knowledge grounding with language models

A very basic API to scrape product reviews from Amazon and get data in real time as JSON with all fields, that amazon product adverstising api does not provide.

Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.

Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

🐙 Guides, papers, lecture, notebooks and resources for prompt engineering

A Python library that helps data scientists to infer causation rather than observing correlation.

Aligning pretrained language models with instruction data generated by themselves.

Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

A community sourced comprehensive database of Australian Post Codes with geolocation data.

Automatically visualize your pandas dataframe via a single print! 📊 💡

Analyze Data with Pandas-based Networks. Documentation:

Library for detecting anomalies in signals

Graph Neural Networks with Keras and Tensorflow 2.

Lime: Explaining the predictions of any machine learning classifier

A Java implementation of Concise Binary Object Representation (RFC 8949)