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Helps teams build, deploy, observe or operate machine-learning systems.

Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.

Open-source Python library enabling ML model inspection and interpretation.

Amadeus Code supports deploying, serving, monitoring, or operating AI and machine-learning systems.

Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.

MLOps in a notebook - uncover insights, surface problems, monitor, and fine tune your models.

ArtificialStudio helps build, test, automate, or manage AI agents, prompts, models, and API workflows.

Drop-in AsyncOpenAI replacement that transparently batches requests via the Batch API for cheaper LLM inference.

Awesome AI Web Search supports machine learning models, deployment, inspection, datasets, or AI development workflows.

Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis).

Open-source project that provides machine-learning models, research, training resources, or evaluation tools.

Inference hosting for AI teams who ship fast and scale faster.

Bayesian Inference Tools in Python.

7B Large Language Model fine-tune by 34B Chinese Character Corpus, based on LLaMA and Alpaca.

An open-source LLM gateway with routing, load balancing, guardrails, and observability for 1000+ models. opensource.

Official inference framework for 1-bit LLMs, by Microsoft. opensource.

BigScience Large Open-science Open-access Multilingual Language Model.

Deploy a ML inference service on a budget in less than 10 lines of code.

BurnRate supports deploying, serving, monitoring, or operating AI and machine-learning systems.

Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.

An easy-to-use feature store. Optimized for time-series data.

Model interpretability and understanding library for PyTorch.

Interactive Hugging Face app that shares a machine-learning model, framework, demonstration or technical resource.

Helps teams build, deploy, observe or operate machine-learning systems.