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Published directory entries matching your search.
GALACTICA is a general-purpose scientific language model trained on scientific text and data. This repository provides a Model API for GALACTICA, installable from pip or the repository, with five model sizes. The models can be used with the transformers library. It is a stand-alone model that is not instruction tuned, so correct prompts are needed for good results.
Build multimodal AI services via cloud native technologies · Model Serving · Generative AI · Neural Search · Cloud Native.
sitemap-module helps generate, validate, or manage XML sitemaps and robots files for search indexing.
Curated list of awesome vector search framework/engine, library, cloud service and research papers to vector similarity search.
Framework that implements AutoML algorithms for model architecture search at scale.
ANGRYsearch is a Linux file search tool that returns instant results as you type, written in Python 3 with a PyQt5 GUI. It offers lite and full modes, and fast, slow and regex search modes. The database and config files are stored locally; indexing about one million files can take roughly two minutes.
Awesome AutoDL is a curated list of automated deep learning resources and an in-depth analysis, subtitled that neural architecture search is not the end. It collects papers, libraries and benchmarks covering neural architecture search and hyper-parameter optimization.
Faiss is a library for efficient similarity search and clustering of dense vectors, containing algorithms that search sets of vectors of any size. It is written in C++ with complete wrappers for Python/numpy, with some algorithms implemented on the GPU, and is developed primarily at Meta's Fundamental AI Research group.
neuml/txtai is an all-in-one AI framework for semantic search, LLM orchestration, and language model workflows. It is open source and hosted on GitHub. The framework provides tools for building applications that understand and generate text.
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.
Vald is a highly scalable distributed vector search engine. It is hosted on GitHub and provides documentation on installation using Helm, requirements, and usage. The project focuses on delivering a scalable solution for vector search.
MemFree is a hybrid AI search engine and AI page generator. It provides accurate answers sourced from the internet and a user's personal knowledge base. It supports multiple AI models, search engines, and input formats including text, images, and local files. It can generate production-ready user interface pages from text or image inputs in seconds.
autoai is an open-source Python framework for automatic artificial intelligence focused on regression and classification tasks over numerical data. It automates model search, hyper-parameter tuning, and generates high-quality Jupyter Notebook code for resulting models.
automl-gs is a Python 3 AutoML module that takes an input CSV and a target field and generates a trained machine learning or deep learning model plus native Python code pipelines. It provides a zero code/model definition interface and performs random hyperparameter searches, reporting metrics for each trial in a CSV.
ch.at is a lightweight language model chat service accessible through HTTP, SSH, DNS, and an OpenAI-compatible API, plus a public agent board with posts, replies, feeds and search. It requires no JavaScript or tracking, and bots are welcome. State is held in RAM only, so a restart loses all data.
Cortex Memory is a production-ready cognitive foundation for autonomous systems such as Embodied-AI and OpenClaw. It provides memory management functionality including extraction, search, and automated optimization, and includes SKILL, CLI, API, MCP, and an insights dashboard out-of-the-box.
Kubeflow Katib is a Kubernetes-native project for automated machine learning (AutoML). It supports hyperparameter tuning, early stopping and neural architecture search, and is agnostic to machine learning frameworks, natively supporting frameworks such as TensorFlow, PyTorch and XGBoost. Training jobs can use any Kubernetes Custom Resources, with out-of-box support for Kubeflow Training Operator, Argo Workflows and Tekton Pipelines. A Python SDK simplifies creating tuning jobs.
LanceDB is a developer-friendly open-source embedded retrieval library for multimodal AI. It emphasizes searching more and managing less. The project tagline is 'Search More; Manage Less.' It is available on GitHub.
LLM App is an open-source project providing ready-to-run cloud templates for retrieval-augmented generation (RAG), AI pipelines and enterprise search with live data. It is Docker-friendly and designed to stay synchronized with data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL and real-time data APIs, hosted by pathwaycom on GitHub.
MeTA is a modern C++ data sciences toolkit. It provides text tokenization including deep semantic features like parse trees, inverted and forward indexes with compression and caching strategies, ranking functions for searching indexes, topic models, classification algorithms, graph algorithms, language models, a CRF implementation for POS-tagging and shallow parsing, and wrappers for liblinear and libsvm.
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.
NNI is an open source AutoML toolkit developed by Microsoft. It automates tasks across the machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning for machine learning workflows.
Open-source vector similarity search for Postgres.
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
