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Showing 227 open source projects for "source"
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Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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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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PokeeResearch-7B
Pokee Deep Research Model Open Source Repo
PokeeResearchOSS provides an open-source, agentic “deep research” model centered on a 7B backbone that can browse, read, and synthesize current information from the web. Instead of relying only on static training data, the agent performs searches, visits pages, and extracts evidence before forming answers to complex queries. It is built to operate end-to-end: planning a research strategy, gathering sources, reasoning over conflicting claims, and writing a grounded response. -
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Stable Diffusion WebUI Docker
Easy Docker setup for Stable Diffusion with user-friendly UI
Stable Diffusion WebUI Docker is a Docker-based repository that simplifies running Stable Diffusion with rich user interfaces by packaging multiple popular web UIs into an easy-to-deploy containerized solution. It integrates leading community UIs like AUTOMATIC1111 and ComfyUI into a Docker Compose setup that can be started with a single command, abstracting away dependency installation and environment configuration. Users can choose which UI profile they want to run — for example, full... -
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CodeGeeX
CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023)
CodeGeeX is a large-scale multilingual code generation model with 13 billion parameters, trained on 850B tokens across more than 20 programming languages. Developed with MindSpore and later made PyTorch-compatible, it is capable of multilingual code generation, cross-lingual code translation, code completion, summarization, and explanation. It has been benchmarked on HumanEval-X, a multilingual program synthesis benchmark introduced alongside the model, and achieves state-of-the-art... -
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GLM-4
GLM-4 series: Open Multilingual Multimodal Chat LMs
GLM-4 is a family of open models from ZhipuAI that spans base, chat, and reasoning variants at both 32B and 9B scales, with long-context support and practical local-deployment options. The GLM-4-32B-0414 models are trained on ~15T high-quality data (including substantial synthetic reasoning data), then post-trained with preference alignment, rejection sampling, and reinforcement learning to improve instruction following, coding, function calling, and agent-style behaviors. The... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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LingBot-VLA
A Pragmatic VLA Foundation Model
LingBot-VLA is an open-source Vision-Language-Action (VLA) foundational AI model designed to serve as a general “brain” for real-world robotic manipulation by grounding multimodal perception and language into actionable motions. It has been pretrained on tens of thousands of hours of real robotic interaction data across multiple robot platforms, which enables it to generalize well to diverse morphologies and tasks without needing extensive retraining on each new bot. -
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GLM-4.6V
GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning
GLM-4.6V represents the latest generation of the GLM-V family and marks a major step forward in multimodal AI by combining advanced vision-language understanding with native “tool-call” capabilities, long-context reasoning, and strong generalization across domains. Unlike many vision-language models that treat images and text separately or require intermediate conversions, GLM-4.6V allows inputs such as images, screenshots or document pages directly as part of its reasoning pipeline — and... -
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NVIDIA Isaac GR00T
NVIDIA Isaac GR00T N1.5 is the world's first open foundation model
NVIDIA Isaac‑GR00T N1.5 is an open-source foundation model engineered for generalized humanoid robot reasoning and manipulation skills. It accepts multimodal inputs—such as language and images—and uses a diffusion transformer architecture built upon vision-language encoders, enabling adaptive robot behaviors across diverse environments. It is designed to be customizable via post-training with real or synthetic data. -
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Phi-3-MLX
Phi-3.5 for Mac: Locally-run Vision and Language Models
Phi-3-Vision-MLX is an Apple MLX (machine learning on Apple silicon) implementation of Phi-3 Vision, a lightweight multi-modal model designed for vision and language tasks. It focuses on running vision-language AI efficiently on Apple hardware like M1 and M2 chips. -
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HY-World 2.0
A Multi-Modal World Model for Reconstructing, Generating, Simulation
HY-World 2.0 is a multi-modal world model framework for reconstructing, generating, and simulating navigable 3D worlds from diverse inputs. It accepts text prompts, single-view images, multi-view images, and videos, and produces 3D world representations rather than limiting output to flat video generation. For text and single-image inputs, it generates high-fidelity 3D Gaussian Splatting scenes through a multi-stage pipeline that includes panorama generation, trajectory planning, world... -
Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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Depth Pro
Sharp Monocular Metric Depth in Less Than a Second
Depth Pro is a foundation model for zero-shot metric monocular depth estimation, producing sharp, high-frequency depth maps with absolute scale from a single image. Unlike many prior approaches, it does not require camera intrinsics or extra metadata, yet still outputs metric depth suitable for downstream 3D tasks. Apple highlights both accuracy and speed: the model can synthesize a ~2.25-megapixel depth map in around 0.3 seconds on a standard GPU, enabling near real-time applications. The... -
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Anthropic SDK Python
Provides convenient access to the Anthropic REST API from any Python 3
The anthropic-sdk-python repository is the official Python client library for interacting with the Anthropic (Claude) REST API. It is designed to provide a user-friendly, type-safe, and asynchronous/synchronous capable interface for making chat/completion requests to models like Claude. The library includes definitions for all request and response parameters using Python typed objects, automatically handles serialization and deserialization, and wraps HTTP logic (timeouts, retries, error... -
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DeepSeek VL2
Mixture-of-Experts Vision-Language Models for Advanced Multimodal
DeepSeek-VL2 is DeepSeek’s vision + language multimodal model—essentially the next-gen successor to their first vision-language models. It combines image and text inputs into a unified embedding / reasoning space so that you can query with text and image jointly (e.g. “What’s going on in this scene?” or “Generate a caption appropriate to context”). The model supports both image understanding (vision tasks) and multimodal reasoning, and is likely used as a component in agent systems to... -
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Qwen3-ASR
Qwen3-ASR is an open-source series of ASR models
Qwen3-ASR is an automatic speech recognition system in the QwenLM family, developed to convert spoken language into text with strong accuracy and real-time performance. As a specialized ASR variant of the broader Qwen language model ecosystem, it focuses on capturing reliable transcriptions from audio sources such as recordings, live streams, or conversational inputs while supporting low latency use cases. The architecture combines advanced neural acoustic modeling with context-aware... -
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DFlash
Block Diffusion for Ultra-Fast Speculative Decoding
DFlash is an open-source framework for ultra-fast speculative decoding using a lightweight block diffusion model to draft text in parallel with a target large language model, dramatically improving inference speed without sacrificing generation quality. It acts as a “drafter” that proposes likely continuations which the main model then verifies, enabling significant throughput gains compared to traditional autoregressive decoding methods that generate token by token. -
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Tongyi DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
DeepResearch (Tongyi DeepResearch) is an open-source “deep research agent” developed by Alibaba’s Tongyi Lab designed for long-horizon, information-seeking tasks. It’s built to act like a research agent: synthesizing, reasoning, retrieving information via the web and documents, and backing its outputs with evidence. The model is about 30.5 billion parameters in size, though at any given token only ~3.3B parameters are active. -
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Stable Virtual Camera
Stable Virtual Camera: Generative View Synthesis with Diffusion Models
Stable Virtual Camera is a multi-view diffusion model developed by Stability AI that transforms 2D images into immersive 3D videos with realistic depth and perspective. Unlike traditional methods that require complex reconstruction or scene-specific optimization, this model allows users to generate novel views from any number of input images and define custom camera trajectories, enabling dynamic exploration of scenes. It supports various aspect ratios and can produce 3D-consistent videos up... -
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GLM-4.5V
GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning
...GLM-4.5V emerged from a training framework that leverages scalable reinforcement learning (with curriculum sampling) to boost performance across tasks ranging from STEM problem solving to long-context reasoning, giving it broad applicability beyond narrow benchmarks. When it was released, it achieved state-of-the-art results on a large collection of public multimodal benchmarks for open-source models. -
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Step-Video-T2V
State-of-the-art (SoTA) text-to-video pre-trained model
...Its training and generation pipeline includes techniques like flow-matching, full 3D attention for temporal consistency, and fine-tuning approaches (e.g. video-based DPO) to improve fidelity and reduce artifacts. As a result, Step-Video-T2V aims to push the frontier of open-source video generation. -
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Qwen3-Omni
Qwen3-omni is a natively end-to-end, omni-modal LLM
...The model supports 119 text languages, 19 speech input languages, and 10 speech output languages. It achieves state-of-the-art results: across 36 audio and audio-visual benchmarks, it hits open-source SOTA on 32 and overall SOTA on 22, outperforming or matching strong closed-source models such as Gemini-2.5 Pro and GPT-4o. To reduce latency, especially in audio/video streaming, Talker predicts discrete speech codecs via a multi-codebook scheme and replaces heavier diffusion approaches. -
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Fara-7B
An Efficient Agentic Model for Computer Use
Fara-7B is a Microsoft initiative aimed at bringing rigor, transparency, and structured evaluation to AI systems through automated and customizable assessment frameworks. It provides stakeholders with a way to benchmark and evaluate models across dimensions such as fairness, robustness, security, privacy, and ethical considerations. Rather than relying on ad-hoc or manual review processes, FARA enables organizations to profile AI behavior using standardized tests, metrics, and reporting... -
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Janus
Unified Multimodal Understanding and Generation Models
Janus is a sophisticated open-source project from DeepSeek AI that aims to unify both visual understanding and image generation in a single model architecture. Rather than having separate systems for “look and describe” and “prompt and generate”, Janus uses an autoregressive transformer framework with a decoupled visual encoder—allowing it to ingest images for comprehension and to produce images from text prompts with shared internal representations. -
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GLM-V
GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning
GLM-V is an open-source vision-language model (VLM) series from ZhipuAI that extends the GLM foundation models into multimodal reasoning and perception. The repository provides both GLM-4.5V and GLM-4.1V models, designed to advance beyond basic perception toward higher-level reasoning, long-context understanding, and agent-based applications. GLM-4.5V builds on the flagship GLM-4.5-Air foundation (106B parameters, 12B active), achieving state-of-the-art results on 42 benchmarks across image, video, document, GUI, and grounding tasks. ... -
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Qwen2.5-Math
A series of math-specific large language models of our Qwen2 series
...Unlike its predecessor Qwen2-Math, Qwen2.5-Math supports both Chain-of-Thought (CoT) reasoning and Tool-Integrated Reasoning (TIR) for solving math problems, and works in both Chinese and English. It is optimized for solving mathematical benchmarks and exams; the 72B-Instruct model achieves state-of-the-art results among open source models on many English and Chinese math tasks. -
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fast-stable-diffusion
Fast-stable-diffusion + DreamBooth
fast-stable-diffusion is a community-curated GitHub repository that provides Colab notebooks and integration examples for running Stable Diffusion and associated UIs like AUTOMATIC1111, ComfyUI, and DreamBooth directly on Google Colab environments. Rather than being a standalone packaged application, this project offers ready-to-use interactive notebooks that install and launch full-feature Stable Diffusion web UIs inside Colab without requiring complex local setups or GPU installations.... -
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OpenAI Privacy Filter
Bidirectional token-classification model for identifiable info
OpenAI Privacy Filter is an open-weight machine learning model designed to detect and mask personally identifiable information in text with high efficiency and contextual awareness. It operates as a bidirectional token classification system that labels sensitive data in a single forward pass rather than generating text sequentially, enabling fast processing for large datasets. The model supports long-context inputs, allowing it to analyze extensive documents without chunking, which improves...
