Popular GitHub Repositories for Experimentation

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

PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ???

Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).

Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms

UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured checks (covering language, code, embedding use-cases), perform root cause analysis on failure cases and give insights on how to resolve them.

Toolkit for efficient experimentation with Speech Recognition, Text2Speech and NLP

? A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.

A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.

??A research-friendly codebase for fast experimentation of single-agent reinforcement learning in JAX ? End-to-End JAX RL

DIAMBRA Arena: a New Reinforcement Learning Platform for Research and Experimentation

GenAIOps with Prompt Flow is a "GenAIOps template and guidance" to help you build LLM-infused apps using Prompt Flow. It offers a range of features including Centralized Code Hosting, Lifecycle Management, Variant and Hyperparameter Experimentation, A/B Deployment, reporting for all runs and experiments and so on.

An experimentation framework for Reinforcement Learning using OpenAI Gym, Tensorflow, and Keras.

NLP library designed for reproducible experimentation management

Generative AI Application Builder on AWS facilitates the development, rapid experimentation, and deployment of generative artificial intelligence (AI) applications without requiring deep experience in AI. The solution includes integrations with Amazon Bedrock and its included LLMs, such as Amazon Titan, and pre-built connectors for 3rd-party LLMs.

Deep-Learning Model Exploration and Development for NLP

A Keras CTC implementation of Baidu's DeepSpeech for model experimentation

PipelineX: Python package to build ML pipelines for experimentation with Kedro, MLflow, and more

Vanilla GAN implemented on top of keras/tensorflow enabling rapid experimentation & research. Branches correspond to implementations of stable GAN variations (i.e. ACGan, InfoGAN) and other promising variations of GANs like conditional and Wasserstein.