Search Results for "source-han" - Page 60
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Showing 2655 open source projects for "source-han"
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AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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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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Mini Agent
A minimal yet professional single agent demo project
Mini-Agent is a minimal yet production-minded demo project that shows how to build a serious command-line AI agent around the MiniMax-M2 model. It is designed both as a reference implementation and as a usable agent, demonstrating a full execution loop that includes planning, tool calls, and iterative refinement. The project exposes an Anthropic-compatible API interface and fully supports interleaved thinking, letting the agent alternate between reasoning steps and tool invocations during... -
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VideoChat
Real-time voice interactive digital human
VideoChat is a real-time voice-interactive “digital human” system that combines automatic speech recognition, large language models, text-to-speech, and talking-head generation into a single conversational pipeline. It supports both pure end-to-end voice solutions based on multimodal large language models (GLM-4-Voice feeding directly into talking-head generation) and a more traditional cascaded pipeline using ASR → LLM → TTS → talking head. It is built as a Gradio Python demo, exposing a... -
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VibeVoice ComfyUI
ComfyUI integration for Microsoft's VibeVoice text-to-speech model
VibeVoice ComfyUI is a comprehensive wrapper that integrates Microsoft’s VibeVoice text-to-speech models directly into ComfyUI workflows. It exposes VibeVoice as a set of custom nodes so you can build single-speaker and multi-speaker voice generation pipelines visually, combining TTS with other audio or generative components. The integration supports high-quality single-speaker synthesis as well as scripted multi-speaker conversations, with optional voice cloning from audio samples for each... -
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SoniTranslate
Synchronized Translation for Videos
SoniTranslate is a video translation and dubbing system that produces synchronized target-language audio tracks for existing video content. It provides a web UI built with Gradio, allowing users to upload a video, choose source and target languages, and then run a pipeline that handles transcription, translation and re-synthesis of speech. Under the hood, it uses advanced speech and diarization models to separate speakers, align audio with timecodes and respect subtitle timing, which lets the generated dub track stay in sync with the original video structure. ... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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AWS Neuron
Powering Amazon custom machine learning chips
AWS Neuron is a software development kit (SDK) for running machine learning inference using AWS Inferentia chips. It consists of a compiler, run-time, and profiling tools that enable developers to run high-performance and low latency inference using AWS Inferentia-based Amazon EC2 Inf1 instances. Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. You can... -
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MiniMax-M1
Open-weight, large-scale hybrid-attention reasoning model
MiniMax-M1 is presented as the world’s first open-weight, large-scale hybrid-attention reasoning model, designed to push the frontier of long-context, tool-using, and deeply “thinking” language models. It is built on the MiniMax-Text-01 foundation and keeps the same massive parameter budget, but reworks the attention and training setup for better reasoning and test-time compute scaling. Architecturally, it combines Mixture-of-Experts layers with lightning attention, enabling the model to... -
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MiniMax-01
Large-language-model & vision-language-model based on Linear Attention
MiniMax-01 is the official repository for two flagship models: MiniMax-Text-01, a long-context language model, and MiniMax-VL-01, a vision-language model built on top of it. MiniMax-Text-01 uses a hybrid attention architecture that blends Lightning Attention, standard softmax attention, and Mixture-of-Experts (MoE) routing to achieve both high throughput and long-context reasoning. It has 456 billion total parameters with 45.9 billion activated per token and is trained with advanced parallel... -
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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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Swirl
Swirl queries any number of data sources with APIs
Swirl queries any number of data sources with APIs and uses spaCy and NLTK to re-rank the unified results without extracting and indexing anything! Includes zero-code configs for Apache Solr, ChatGPT, Elastic Search, OpenSearch, PostgreSQL, Google BigQuery, RequestsGet, Google PSE, NLResearch.com, Miro & more! SWIRL adapts and distributes queries to anything with a search API - search engines, databases, noSQL engines, cloud/SaaS services etc - and uses AI (Large Language Models) to re-rank... -
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Darts
A python library for easy manipulation and forecasting of time series
darts is a Python library for easy manipulation and forecasting of time series. It contains a variety of models, from classics such as ARIMA to deep neural networks. The models can all be used in the same way, using fit() and predict() functions, similar to scikit-learn. The library also makes it easy to backtest models, combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models... -
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Hunyuan3D-1
A Unified Framework for Text-to-3D and Image-to-3D Generation
...It provides a framework combining shape generation and texture synthesis, enabling users to create 3D assets from images or text conditions. While less advanced than version 2.1, it laid the foundations for the later PBR, higher resolution, and open-source enhancements. (Note: less detailed public documentation was found for Hunyuan3D-1 compared to 2.1.). Community and ecosystem support (e.g. usage via Blender addon for geometry/texture). Integration into user-friendly tools/platforms. -
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Qwen2.5-Omni
Capable of understanding text, audio, vision, video
Qwen2.5-Omni is an end-to-end multimodal flagship model in the Qwen series by Alibaba Cloud, designed to process multiple modalities (text, images, audio, video) and generate responses both as text and natural speech in streaming real-time. It supports “Thinker-Talker” architecture, and introduces innovations for aligning modalities over time (for example synchronizing video/audio), robust speech generation, and low-VRAM/quantized versions to make usage more accessible. It holds... -
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Poetiq
Reproduction of Poetiq's record-breaking submission to the ARC-AGI-1
poetiq-arc-agi-solver is the open-source codebase from Poetiq that replicates their record-breaking submission to the challenging benchmark suite ARC-AGI (both ARC-AGI-1 and ARC-AGI-2). The project demonstrates a system that orchestrates large language models (LLMs) — like those from major providers — with carefully engineered prompting, reasoning workflows, and dynamic strategies, to tackle the abstract, logic-heavy problems in ARC-AGI. -
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Cherche
Neural Search
Cherche allows the creation of efficient neural search pipelines using retrievers and pre-trained language models as rankers. Cherche's main strength is its ability to build diverse and end-to-end pipelines from lexical matching, semantic matching, and collaborative filtering-based models. Cherche provides modules dedicated to summarization and question answering. These modules are compatible with Hugging Face's pre-trained models and fully integrated into neural search pipelines. Search is... -
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h2oGPT
Private chat with local GPT with document, images, video, etc.
h2oGPT is an open-source platform that allows users to interact with local GPT models in a completely private environment. It supports a variety of document types, including PDFs, Word files, images, video frames, and even audio, enabling users to query and analyze their documents or engage in a private chat with AI. The platform is designed to be secure and offline, ensuring that all data remains private and under the user's control. h2oGPT supports several AI models, including oLLaMa and Mixtral, making it a flexible tool for anyone needing advanced document analysis and AI-driven conversation in a secure, local setup. -
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Kimi-Audio
Audio foundation model excelling in audio understanding
Kimi-Audio is an ambitious open-source audio foundation model designed to unify a wide array of audio processing tasks — from speech recognition and audio understanding to generative conversation and sound event classification — within a single cohesive architecture. Instead of fragmenting work across specialized models, Kimi-Audio handles automatic speech recognition (ASR), audio question answering, automatic audio captioning, speech emotion recognition, and audio-to-text chat in one system, enabling developers to build rich, multimodal audio applications without stitching together disparate components. ... -
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machine_learning_examples
A collection of machine learning examples and tutorials
machine_learning_examples is an open-source repository that provides a large collection of machine learning tutorials and practical code examples. The project aims to teach machine learning concepts through hands-on programming rather than purely theoretical explanations. It includes implementations of many machine learning algorithms and neural network architectures using Python and popular libraries such as TensorFlow and NumPy. -
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ML-NLP
This project is a common knowledge point and code implementation
ML-NLP is a large open-source repository that collects theoretical knowledge, practical explanations, and code examples related to machine learning, deep learning, and natural language processing. The project is designed primarily as a learning resource for algorithm engineers and students preparing for technical interviews in machine learning or NLP roles. It compiles important concepts that frequently appear in machine learning discussions, including neural network architectures, training methods, and common algorithmic techniques. ... -
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ML Retreat
Machine Learning Journal for Intermediate to Advanced Topics
ML Retreat is an open-source learning repository that serves as a structured journal documenting advanced topics in machine learning and artificial intelligence. The project compiles detailed notes, technical explanations, and curated resources that guide readers through complex concepts across modern AI research. Rather than functioning as a traditional tutorial series, the repository is organized as a learning journey that progressively explores increasingly advanced subjects. ... -
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LLMSurvey
A Survey of Large Language Models
LLMSurvey is an open-source research repository that aggregates academic papers, resources, and references related to large language models. The project is closely associated with the academic survey titled “A Survey of Large Language Models,” which provides a comprehensive overview of the development, architecture, capabilities, and societal implications of modern LLMs. -
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The Hypersim Dataset
Photorealistic Synthetic Dataset for Holistic Indoor Scene
Hypersim is a large-scale, photorealistic synthetic dataset and tooling suite for indoor scene understanding research. It provides richly annotated renderings—RGB, depth, surface normals, instance and semantic segmentations, and material/lighting metadata—produced from high-fidelity virtual environments. The dataset spans diverse furniture layouts, room types, and camera trajectories, enabling robust training for geometry, segmentation, and SLAM-adjacent tasks. Rendering pipelines and... -
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AI Agent Deep Dive
AI Agent Source Code Deep Research Report
AI Agent Deep Dive is a comprehensive educational repository designed to provide a deep and structured understanding of how modern AI agents work, focusing on architecture, workflows, and real-world implementation patterns. It breaks down complex concepts such as planning, tool usage, memory management, and multi-step reasoning into digestible explanations and practical examples. The project is organized as a learning resource rather than a standalone framework, making it particularly useful... -
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CUDA Containers for Edge AI & Robotics
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
CUDA Containers for Edge AI & Robotics is an open-source project that provides a modular container build system designed for running machine learning and AI workloads on NVIDIA Jetson devices. The repository contains container configurations that package the latest AI frameworks and dependencies optimized for Jetson hardware. These containers simplify the deployment of complex machine learning environments by bundling libraries such as CUDA, TensorRT, and deep learning frameworks into reproducible container images. ... -
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python-small-examples
Focus on creating classic Python small examples and cases
python-small-examples is an open-source educational repository that contains hundreds of concise Python programming examples designed to illustrate practical coding techniques. The project focuses on teaching programming concepts through small, focused scripts that demonstrate common tasks in data processing, visualization, and general programming. Each example highlights a specific function or programming pattern so that learners can quickly understand how to apply Python features in real-world scenarios. ... -
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R-KV
Redundancy-aware KV Cache Compression for Reasoning Models
R-KV is an open-source research project that focuses on improving the efficiency of large language model inference through key-value cache compression techniques. Modern transformer models rely heavily on KV caches during autoregressive decoding, which store intermediate attention states to accelerate generation. However, these caches can consume large amounts of memory, especially in reasoning-oriented models with long context windows.