Search Results for "domain" - Page 2
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Showing 548 open source projects for "domain"
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Label Sleuth
Open source no-code system for text annotation and building of text
An open-source no-code system for text annotation and building text classifiers. No AI knowledge needed. From task definition to working model in just a few hours! While domain experts label their data, Label Sleuth automatically trains in the background-appropriate machine learning models. To avoid wasted labeling effort, Label Sleuth employs active learning techniques to guide the user in what they should be labeled next. Domain experts can quickly start labeling their data through an intuitive user interface. ... -
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TAME LLM
Traditional Mandarin LLMs for Taiwan
...The project includes models such as Llama-3-Taiwan-70B, which are fine-tuned versions of large transformer architectures trained on extensive corpora containing both Traditional Mandarin and English text. These models are designed to support applications such as conversational AI, knowledge retrieval, and domain-specific reasoning in fields like manufacturing, law, healthcare, and electronics. The training pipeline leverages high-performance computing infrastructure and frameworks such as NVIDIA NeMo and Megatron to enable large-scale model training. Taiwan-LLM aims to improve language understanding and generation for Traditional Mandarin users by incorporating region-specific datasets and evaluation benchmarks. -
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DeepSearcher
Open Source Deep Research Alternative to Reason and Search
...The project integrates with vector databases (including Milvus and related options) so organizations can index internal documents and query them with semantic retrieval. It also supports flexible embeddings, making it easier to choose different embedding models depending on domain requirements, latency targets, or accuracy goals. The overall workflow aims to minimize hallucinations by grounding outputs in retrieved material and then applying structured reasoning over that evidence before generating a final report. -
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MetaCLIP
ICLR2024 Spotlight: curation/training code, metadata, distribution
MetaCLIP is a research codebase that extends the CLIP framework into a meta-learning / continual learning regime, aiming to adapt CLIP-style models to new tasks or domains efficiently. The goal is to preserve CLIP’s strong zero-shot transfer capability while enabling fast adaptation to domain shifts or novel class sets with minimal data and without catastrophic forgetting. The repository provides training logic, adaptation strategies (e.g. prompt tuning, adapter modules), and evaluation across base and target domains to measure how well the model retains its general knowledge while specializing as needed. It includes utilities to fine-tune vision-language embeddings, compute prompt or adapter updates, and benchmark across transfer and retention metrics. ... -
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TorchIO
Medical imaging toolkit for deep learning
...Transforms include typical computer vision operations such as random affine transformations and also domain-specific ones such as simulation of intensity artifacts due to MRI magnetic field inhomogeneity. -
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MedicalGPT
MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training
MedicalGPT training medical GPT model with ChatGPT training pipeline, implementation of Pretraining, Supervised Finetuning, Reward Modeling and Reinforcement Learning. MedicalGPT trains large medical models, including secondary pre-training, supervised fine-tuning, reward modeling, and reinforcement learning training. -
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openbench
Provider-agnostic, open-source evaluation infrastructure
...With a simple CLI interface (e.g. bench eval <benchmark> --model <model-id>), you can quickly evaluate any model supported by Groq or other providers (OpenAI, Anthropic, HuggingFace, local models, etc.). openbench also supports private/local evaluations: you can integrate your own custom benchmarks or data (e.g. internal test suites, domain-specific tasks) to evaluate models in a privacy-preserving way. -
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OpenAGI
When LLM Meets Domain Experts
OpenAGI is a package for AI agent creation designed to connect large language models with domain-specific tools and workflows in the AIOS (AI Operating System) ecosystem. It provides a structured Python framework, pyopenagi, for defining agents as modular units that encapsulate execution logic, configuration, and dependency metadata. Agents are organized in a well-defined folder structure that includes code (agent.py), configuration (config.json), and extra requirements (meta_requirements.txt), which makes them easy to package, share, and reuse. ... -
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TorchRec
Pytorch domain library for recommendation systems
TorchRec is a PyTorch domain library built to provide common sparsity & parallelism primitives needed for large-scale recommender systems (RecSys). It allows authors to train models with large embedding tables sharded across many GPUs. Parallelism primitives that enable easy authoring of large, performant multi-device/multi-node models using hybrid data-parallelism/model-parallelism. -
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DGL
Python package built to ease deep learning on graph
...Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed training infrastructure. DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others. We are keen to bringing graphs closer to deep learning researchers. We want to make it easy to implement graph neural networks model family. We also want to make the combination of graph based modules and tensor based modules (PyTorch or MXNet) as smooth as possible. ... -
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GLM-4-Voice
GLM-4-Voice | End-to-End Chinese-English Conversational Model
GLM-4-Voice is an open-source speech-enabled model from ZhipuAI, extending the GLM-4 family into the audio domain. It integrates advanced voice recognition and generation with the multimodal reasoning capabilities of GLM-4, enabling smooth natural interaction via spoken input and output. The model supports real-time speech-to-text transcription, spoken dialogue understanding, and text-to-speech synthesis, making it suitable for conversational AI, virtual assistants, and accessibility applications. ... -
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CogView4
CogView4, CogView3-Plus and CogView3(ECCV 2024)
CogView4 is the latest generation in the CogView series of vision-language foundation models, developed as a bilingual (Chinese and English) open-source system for high-quality image understanding and generation. Built on top of the GLM framework, it supports multimodal tasks including text-to-image synthesis, image captioning, and visual reasoning. Compared to previous CogView versions, CogView4 introduces architectural upgrades, improved training pipelines, and larger-scale datasets,... -
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Claude Code Plugins Directory
Official, Anthropic-managed directory of high quality Claude Plugins
...These plugins define how Claude should access tools, retrieve data, and execute structured tasks so that outputs become more consistent and production-ready. The project emphasizes customizable automation by allowing developers to encode preferred workflows, domain knowledge, and operational rules directly into plugin configurations. It is built to work with Claude Cowork and Claude Code environments, enabling teams to standardize how AI assistance behaves across different use cases. By exposing slash commands and workflow logic, the repository helps organizations operationalize AI in real business contexts rather than relying on generic prompting. -
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GitHub520
Community-maintained approach to improving access to GitHub services
GitHub520 is a community-maintained approach to improving access to GitHub services from regions with network friction by leveraging host mappings. The repository provides a regularly updated list of domain-to-IP entries meant to be appended to a system’s hosts file so certain GitHub endpoints resolve faster or more reliably. It includes scripts or guidance to automate updates, reducing the need for manual lookups when IPs change. The project’s goal is pragmatic: improve developer productivity by mitigating timeouts and slow asset retrieval during cloning, package installs, or browsing. ... -
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Raccoon
High-performance reconnaissance and vulnerability scanning tool
Raccoon is a high-performance offensive security tool designed to assist with reconnaissance and vulnerability scanning during penetration testing and security assessments. It automates several common reconnaissance tasks, allowing security professionals to quickly gather information about a target system or web application. The tool combines multiple scanning techniques into a single workflow, helping users identify potential weaknesses, exposed services, and accessible resources on a... -
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Google Research
This repository contains code released by Google Research
Google Research is a massive monorepo that hosts a wide range of research code released by Google Research teams across machine learning, artificial intelligence, robotics, natural language processing, and other advanced domains. Rather than being a single framework, the repository serves as a centralized collection of experimental projects, reference implementations, and reproducible research artifacts. It is intended primarily for researchers and advanced practitioners who want to explore... -
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VibeThinker
Diversity-driven optimization and large-model reasoning ability
...It contains about 1.5 billion parameters, far smaller than many “frontier” models, yet it is explicitly optimized for reasoning, mathematics, and code generation tasks rather than general open-domain chat. The innovation lies in its training methodology: the team uses what they call the Spectrum-to-Signal Principle (SSP), where a first stage emphasizes diversity of reasoning paths (the “spectrum” phase) and a second stage uses reinforcement techniques (the “signal” phase) to refine toward correctness and strong reasoning. The result is a model that outpaces many much larger models on domain-specific benchmarks, demonstrating that smaller models, if trained carefully and with the right objectives, can achieve high performance in reasoning-centric tasks. -
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WhatBreach
OSINT tool for discovering email addresses in known data breaches
WhatBreach is an open source OSINT (Open Source Intelligence) tool designed to help users discover whether an email address has appeared in known data breaches. It simplifies the process of investigating compromised credentials by allowing users to search for a single email address or analyze multiple email addresses at once. It gathers breach information from various sources and APIs to identify where the email has been exposed in leaked databases or online paste sites. Once breaches are... -
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Claude Scientific Skills
A set of ready to use Agent Skills for research, science, engineering
...Its primary goal is to reduce the friction of scientific computing by giving AI agents structured access to specialized libraries, databases, and research pipelines. Overall, the repository acts as a modular capability layer that transforms general AI agents into domain-aware computational scientists. -
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AWS MCP Servers
Helping you get the most out of AWS, wherever you use MCP
AWS MCP Servers are a collection of remotely hosted, fully-managed Model Context Protocol (MCP) servers by AWS, providing AI applications with real-time access to AWS documentation, API references, best practices, and infrastructure-management capabilities via natural-language workflows. An MCP Server is a lightweight program that exposes specific capabilities through the standardized Model Context Protocol. Host applications (such as chatbots, IDEs, and other AI tools) have MCP clients that... -
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SciSpaCy
A full spaCy pipeline and models for scientific/biomedical documents
ScispaCy is a spaCy extension optimized for processing biomedical and scientific text, providing domain-specific NLP models for tasks like named entity recognition (NER) and dependency parsing. -
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WordOps
Install and manage a high performance WordPress stack
An essential toolset that eases WordPress site and server administration. -
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TorchAudio
Data manipulation and transformation for audio signal processing
The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch operations which makes it easy to use and feel like a natural extension. -
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LangExtract
A Python library for extracting structured information
LangExtract is a Python library developed by Google that leverages large language models (LLMs) to extract structured information from unstructured text—such as clinical notes, research papers, or literary works—based on user-defined instructions. It is designed to transform free-form text into reliable, schema-constrained data while maintaining traceability back to the source material. Each extracted entity is precisely grounded in its original context, allowing visual inspection and... -
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R1-V
Witness the aha moment of VLM with less than $3
...The project focuses on building a comprehensive framework that emphasizes algorithm enhancement, efficiency optimization, and task diversity to achieve general vision-language intelligence and visual/GUI agents. The team's long-term goal is to contribute impactful open-source research in this domain.
