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Smart code context extractor for AI assistants with accurate token counting and budget management.

Python script to extract savefiles out of Xbox Game Pass for PC games

Eurybia monitors data and model drift over time and securizes model deployment with data validation.

Models.dev is a GitHub repository or organization with source code, releases, documentation, or project resources.

Open-source platform for high-performance ML model serving.

Unsupervised machine learning with multivariate Gaussian mixture model.

Go binding for MXNet c predict api to do inference with a pre-trained model.

Build multimodal AI services via cloud native technologies · Model Serving · Generative AI · Neural Search · Cloud Native.

Open source MLOps project that eases model handoffs between data scientist and DevOps.

Inspired on Private GPT with the GPT4ALL model replaced with the Vicuna-7B model and using the InstructorEmbeddings instead of LlamaEmbeddings.

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

Machine learning model serving framework with dynamic batching and pipelined stages, provides an easy-to-use Python interface.

Python-free Rust inference server with OpenAI API compatibility and hot model swapping.

An MLOps/LLMOps platform for model building, evaluation, and fine-tuning.

Suite of tools that users, both novice and advanced, can use to optimize machine learning models for deployment and execution.

Large Language Model Text Generation Inference.

A machine learning / bayesian inference assigning attributes to objects.

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

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

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.

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

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

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