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NASGym is a proof-of-concept OpenAI Gym environment for Neural Architecture Search. It implements reinforcement learning steps for NAS and encodes networks using the Neural Structure Code from BlockQNN. A network is modeled as a list of NSCs, an action adds a layer, and the reward is accuracy after early-stop training. CIFAR-10 is the default dataset. The code and documentation may contain minor bugs.
NCNN is a neural network inference framework optimized for mobile, embedded, and desktop deployment. It has no third-party runtime dependencies and runs across CPU and Vulkan GPU backends. Tools such as pnnx convert PyTorch and ONNX models to ncnn, allowing deployment to phones, PCs, browsers, and edge devices. The project is used in several Tencent applications.
NDScala is a Scala 3 library for N-dimensional and multi-dimensional arrays (tensors), described as comparable to NumPy ndarray or PyTorch Tensor, with type safety over shapes, array and axis labels and numeric data types. The repository includes materials on shape-safe neural network training and an ONNXScala component.
Easy-to-use library to boost AI inference.
Neuraxle is an AutoML library that supports hyperparameter tuning via pipeline abstractions to build clean deep learning production pipelines. Pipeline steps can have associated hyperparameter spaces, and the library is compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks, and MLOps environments.
Nimblebox supports deploying, serving, monitoring, or operating AI and machine-learning systems.
An Easy-to-Use and High-Performance AI deployment framework.
Nos is an open-source module for running AI workloads on Kubernetes, intended to increase GPU utilization, cut infrastructure costs and improve workload performance. It provides dynamic GPU partitioning and elastic resource quota management.
Neural networks framework in pure C: training and inference, no dependencies.
NVIDIA AI is a suite of enterprise artificial intelligence solutions offered by NVIDIA. The portfolio includes accelerated infrastructure, enterprise-grade software, and AI models. Solution areas span agentic AI, inference, conversational AI, data science, and cybersecurity. The program aims to help organizations transform into AI-enabled enterprises.
NVIDIA NIM is a catalog of models offered as inference microservices for deployment on the user's GPU infrastructure. The listings include downloadable models and free or partner endpoints, organized by use cases such as image generation, speech-to-text and drug discovery.
Simplifies and accelerates MLOps by bridging the gap between ML models and edge hardware.
onWatch is an open-source tool developed by onllm-dev that tracks AI API quotas for services including Synthetic, Z.ai, Anthropic Claude Code, Codex, GitHub Copilot and Antigravity in real time. It functions as a lightweight background daemon that uses less than 50MB of RAM, stores data in SQLite, and provides a Material Design 3 dashboard. The tool does not collect telemetry.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
OpenLIT is an open-source agent harness engineering platform built on OpenTelemetry. It provides tracing, evaluations, guardrails, prompt and context management, and cost and GPU monitoring for the harness around AI agents and coding agents. It is free to self-host under Apache 2.0 and is described as working with many models, frameworks and harnesses.
Turns your ML code into microservices with web API, interactive GUI, and more.
Platform and SDK for AI Engineers providing tools for LLM evaluation, observability, and a version-controlled enhanced prompt playground.
Parris, the automated infrastructure setup tool for machine learning algorithms.
pgvecto.rs is an open-source tool that provides scalable, low-latency, hybrid-enabled vector search for PostgreSQL. It is designed to enhance vector search capabilities without modifying the core database system, per its official GitHub repository.
Open-source vector similarity search for Postgres.
Pipeline Conversations is a podcast from ZenML featuring interviews with platform engineers, ML practitioners and technical leaders building production AI systems. Episodes cover MLOps and LLMOps topics including Kubernetes workflows, model fine-tuning and evaluation, LLM security, cost optimization, prompt engineering and agents in production.
Portkey is a production stack for generative AI builders that offers a suite of tools including an AI gateway, observability features, guardrails and prompt management modules. It is designed to help organizations democratize and productionize generative AI.
A workflow management system, designed for modern infrastructure.
pyhsmm is a Python library for approximate unsupervised inference in Bayesian Hidden Markov Models and explicit-duration Hidden semi-Markov Models, focusing on the HDP-HMM and HDP-HSMM with weak-limit approximations. Extensions include autoregressive models, switching linear dynamical systems and factorial models. The package is stated as no longer maintained and was last tested with Python 3.7.
