Search Results for "ai" - Page 42
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Showing 1706 open source projects for "ai"
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TokenSpeed
TokenSpeed is a speed-of-light LLM inference engine
...It builds on ideas and components from the broader open-source inference ecosystem while presenting its own execution stack. TokenSpeed is useful for developers building local or server-side LLM infrastructure for agents, coding systems, and high-volume AI applications. Its main value is providing an inference layer optimized for fast token generation under practical agent workloads. -
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KeepChatGPT
Browser userscript that enhances ChatGPT reliability and usability
...It runs through userscript managers and injects additional functionality directly into the page, allowing users to improve their workflow without requiring a backend service or separate application. It focuses on solving common problems experienced during AI conversations, such as session timeouts, network errors, message failures, and interruptions during long chats. By automating session refresh and maintaining active connections, KeepChatGPT reduces the need for repeated manual steps when recovering from errors or expired sessions. KeepChatGPT also introduces a variety of enhancements that improve the overall interface and user experience, including page cleanup, expanded display layouts, conversation cloning, and detailed chat information. -
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SageAttention
NeurIPS2025 Spotlight] Quantized Attention
SageAttention is an open-source optimization library designed to accelerate the attention mechanism used in transformer-based neural networks. Since attention operations are often the most computationally expensive component of modern AI models, SageAttention introduces quantization techniques that significantly reduce computational overhead while preserving model accuracy. The system achieves this by using low-precision numerical formats such as INT4, FP8, or INT8 to represent key matrices within the attention computation. These optimizations allow models to perform matrix operations faster and consume less memory during inference. ... -
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Llama-Chinese
Llama Chinese community, real-time aggregation
...It also provides optimized versions of LLaMA models trained on large-scale Chinese datasets to improve performance in tasks such as translation, summarization, and conversational AI. The community maintains educational materials and technical documentation that help researchers understand the process of training and deploying Chinese-optimized large language models. In addition to model development, the project collects learning resources and open research contributions related to LLM technology in Chinese environments. ... -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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AReal
Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible
...It is intended to facilitate reproducible RL training on reasoning / agentic tasks, supporting scaling from single nodes to large GPU clusters. It can streamline the development of AI agents and reasoning systems. Support for algorithm and system co-design optimizations (to improve efficiency and stability). -
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NVIDIA Isaac Sim
NVIDIA Isaac Sim is an open-source application on NVIDIA Omniverse
NVIDIA Isaac Sim is a high-fidelity robotics simulation platform built on NVIDIA Omniverse to develop, test, and validate AI-driven robots in physically accurate virtual environments. It supports a wide array of robotics formats (URDF, MJCF, CAD), includes GPU-accelerated physics, and features immersive RTX rendering and multisensory simulation. Realistic physics via GPU-accelerated engines and RTX ray tracing. Multi-sensor simulation (RGB-D cameras, Lidar, Radar, IMU, contact sensors). ... -
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Giskard
Collaborative & Open-Source Quality Assurance for all AI models
The testing framework dedicated to ML models, from tabular to LLMs. Giskard is an open-source testing framework dedicated to ML models, from tabular models to LLMs. Testing Machine Learning applications can be tedious. Since ML models depend on data, testing scenarios depend on the domain specificities and are often infinite. At Giskard, we believe that Machine Learning needs its own testing framework. Created by ML engineers for ML engineers, Giskard enables you to scan your model to find... -
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Materials Discovery: GNoME
AI discovers 520000 stable inorganic crystal structures for research
Materials Discovery (GNoME) is a large-scale research initiative by Google DeepMind focused on applying graph neural networks to accelerate the discovery of stable inorganic crystal materials. The project centers on Graph Networks for Materials Exploration (GNoME), a message-passing neural network architecture trained on density functional theory (DFT) data to predict material stability and energy formation. Using GNoME, DeepMind identified 381,000 new stable materials, later expanding the... -
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turbovec
A vector index built on TurboQuant, written in Rust with Python
...It avoids a separate training phase for the quantizer, which can simplify setup compared with systems that require codebook learning. TurboVec is useful for developers building retrieval, ranking, semantic search, recommendation, or AI memory systems. Its main value is combining Rust performance with a Python-facing workflow for modern vector search experiments and applications. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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NeuTTS Nano
On-device TTS model by Neuphonic
...NeuTTS is especially useful for embedded voice agents, private assistants, toys, accessibility tools, and compliance-sensitive apps. Its main value is making modern voice AI more portable, private, and practical for local deployment. -
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LitGPT
20+ high-performance LLMs with recipes to pretrain, finetune at scale
LitGPT is a collection of over 20 high-performance large language models (LLMs) accompanied by recipes to pretrain, finetune, and deploy them at scale. It provides implementations without abstractions, making it beginner-friendly while offering advanced features like flash attention and support for various precision levels. LitGPT is designed to run efficiently across multiple GPUs or TPUs, catering to both small-scale and large-scale deployments. -
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DataProfiler
Extract schema, statistics and entities from datasets
DataProfiler is an AI-powered tool for automatic data analysis and profiling, designed to detect patterns, anomalies, and schema inconsistencies in structured and unstructured datasets. The DataProfiler is a Python library designed to make data analysis, monitoring, and sensitive data detection easy. Loading Data with a single command, the library automatically formats & loads files into a DataFrame. -
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Robusta
Kubernetes observability and automation
Keep your Kubernetes microservices up and running. Connect your existing Prometheus, gain 360° observability. Robusta is both an automation engine for Kubernetes and a multi-cluster observability platform. Robusta is commonly used alongside Prometheus, but other tools are supported too. By listening to all the events in your cluster, Robusta can tell you why alerts fired, what happened at the same time, and what you can do about it. Robusta can either improve your existing alerts or be used... -
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Frontend Slides
Create beautiful slides on the web using Claude's frontend skills
...It also supports converting existing PowerPoint files into web-based presentations while preserving content such as images, text, and structure. The tool includes curated design presets that avoid generic AI-generated aesthetics, ensuring presentations feel distinctive and intentional. Its architecture uses progressive disclosure, loading only necessary components at each step to keep the workflow efficient and intuitive. -
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Guardrails
Framework for validating and controlling LLM outputs in AI apps
Guardrails is an open source Python framework designed to help developers build more reliable and controlled applications powered by large language models. It provides mechanisms for validating and constraining both the inputs sent to a model and the outputs generated by it, helping reduce risks such as harmful content, prompt injection, or inaccurate responses. Guardrails works by applying configurable guards that intercept and evaluate interactions with the model before results are... -
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FlexLLMGen
Running large language models on a single GPU
...The architecture distributes computation and memory usage across the GPU, CPU, and disk in order to maximize the number of tokens processed during inference. This design allows organizations to deploy powerful language models for high-volume tasks without the infrastructure costs typically associated with large-scale AI systems. The project is particularly useful for workloads that prioritize throughput over latency, including benchmarking experiments and large corpus analysis. -
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NExT-GPT
Code and models for ICML 2024 paper, NExT-GPT
NExT-GPT is an open-source research framework that implements an advanced multimodal large language model capable of understanding and generating content across multiple modalities. Unlike traditional models that primarily handle text, NExT-GPT supports input and output combinations involving text, images, video, and audio in a unified architecture. The system connects a large language model with multimodal encoders and diffusion-based decoders so it can interpret information from different... -
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Xtuner
A Next-Generation Training Engine Built for Ultra-Large MoE Models
...Its architecture incorporates memory-efficient optimizations that allow researchers to train large models even when computational resources are limited. XTuner is also designed to integrate with modern AI ecosystems, supporting multimodal training, reinforcement learning optimization, and instruction tuning pipelines. -
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MoCo (Momentum Contrast)
Self-supervised visual learning using momentum contrast in PyTorch
MoCo is an open source PyTorch implementation developed by Facebook AI Research (FAIR) for the papers “Momentum Contrast for Unsupervised Visual Representation Learning” (He et al., 2019) and “Improved Baselines with Momentum Contrastive Learning” (Chen et al., 2020). It introduces Momentum Contrast (MoCo), a scalable approach to self-supervised learning that enables visual representation learning without labeled data. -
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Anima
Open-source Agent OS for hardware intelligence
Anima is an open-source Agent OS designed to make hardware behave more intelligently. Instead of acting as a basic smart-home control panel, it gives connected devices perception, memory, decision-making, and extensible AI capabilities. The system runs as an intelligent hardware agent runtime inside the local network. It discovers devices, tracks their state, and controls real hardware through adapters. Anima uses an LLM-powered brain to interpret the environment, user intent, memory, and device-specific skills before planning actions. It currently supports Mi Home and MIoT devices while providing a dashboard, REST API, and CLI for observation, debugging, control, and extension. -
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Defending Code Reference Harness
Skills for threat modeling, scanning, triage, patching, etc.
...The overall architecture is meant to be adaptable, so teams can modify it for other languages, bug classes, and detection systems. Its main value is giving defenders a practical framework for exploring AI-assisted secure code review and remediation. -
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Intel Extension for PyTorch
A Python package for extending the official PyTorch
...Optimizations take advantage of Intel® Advanced Vector Extensions 512 (Intel® AVX-512) Vector Neural Network Instructions (VNNI) and Intel® Advanced Matrix Extensions (Intel® AMX) on Intel CPUs as well as Intel Xe Matrix Extensions (XMX) AI engines on Intel discrete GPUs. Moreover, Intel® Extension for PyTorch* provides easy GPU acceleration for Intel discrete GPUs through the PyTorch* xpu device. -
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OpenLLM
Operating LLMs in production
...Fine-tune, serve, deploy, and monitor any LLMs with ease. With OpenLLM, you can run inference with any open-source large-language models, deploy to the cloud or on-premises, and build powerful AI apps. Built-in supports a wide range of open-source LLMs and model runtime, including Llama 2， StableLM, Falcon, Dolly, Flan-T5, ChatGLM, StarCoder, and more. Serve LLMs over RESTful API or gRPC with one command, query via WebUI, CLI, our Python/Javascript client, or any HTTP client. -
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claude-real-video
Let Claude (or any LLM) actually watch a video
claude-real-video is a local video processing tool that prepares videos for analysis by Claude or other LLMs. It accepts public video URLs or local files and extracts the visual and audio evidence an AI model needs. Instead of sampling at a fixed interval, it detects scene changes and removes near-duplicate frames to reduce unnecessary token usage. It can transcribe audio, generate a clean output folder, and create a local viewer with the video, keyframe grid, and transcript. The tool can also be installed as a Claude Code skill so an agent can process videos more directly. ... -
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whichllm
Find the local LLM that actually runs and performs best
...The project is useful for users who are unsure which local LLM will perform well on their system. It focuses on real, recency-aware benchmarks so recommendations better reflect current model performance. whichllm is especially helpful for developers, AI hobbyists, and researchers comparing local inference options across NVIDIA, AMD, Apple Silicon, and CPU-only environments. Its main value is reducing guesswork when choosing a local model to download and run.
