Search Results for "input-output model"
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Showing 584 open source projects for "input-output model"
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ModelContextProtocol.NET
A C# SDK implementation of the Model Context Protocol (MCP)
ModelContextProtocol.NET is a C# SDK that implements the Model Context Protocol (MCP), allowing developers to build MCP servers on the .NET platform. It supports standard input/output communication and provides a framework for tool integration. The SDK is compatible with Native AOT, enhancing performance and deployment flexibility. A calculator demo implementation is included to demonstrate its capabilities. -
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MCPTools
A command-line interface for interacting with MCP
mcptools is a command-line interface designed for interacting with Model Context Protocol (MCP) servers using both standard input/output and HTTP transport methods. It allows users to discover and call tools, list resources, and interact with MCP-compatible servers. The tool supports various output formats and includes features like an interactive shell, project scaffolding, and server alias management. -
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MCP Shell Server
Shell command execution server implementing the Model Context Protocol
A secure shell command execution server implementing the Model Context Protocol (MCP), allowing remote execution of whitelisted shell commands with support for standard input. -
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iTerm MCP
A Model Context Protocol server that executes commands
A Model Context Protocol server that executes commands in the current iTerm session, providing AI assistants with the ability to interact with REPL environments and command-line interfaces. -
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EduCDM
The Model Zoo of cognitive diagnosis models
The Model Zoo of Cognitive Diagnosis Models, including classic Item Response Ranking (IRT), Multidimensional Item Response Ranking (MIRT), Deterministic Input, Noisy "And" model(DINA), and advanced Fuzzy Cognitive Diagnosis Framework (FuzzyCDF), Neural Cognitive Diagnosis Model (NCDM), Item Response Ranking framework (IRR), Incremental Cognitive Diagnosis (ICD) and Knowledge-association baesd extension of NeuralCD (KaNCD). -
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Bytewax
Python Stream Processing
...Connect data sources, run stateful transformations, and write to various downstream systems with built-in connectors or existing Python libraries. Bytewax is a Python framework and Rust distributed processing engine that uses a dataflow computational model to provide parallelizable stream processing and event processing capabilities similar to Flink, Spark, and Kafka Streams. You can use Bytewax for a variety of workloads from moving data à la Kafka Connect style all the way to advanced online machine learning workloads. Bytewax is not limited to streaming applications but excels anywhere that data can be distributed at the input and output. -
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Actors MCP Server
Model Context Protocol (MCP) Server for Apify's Actors
The Apify Actors MCP Server is a Model Context Protocol (MCP) server that enables AI assistants to interact with Apify Actors. This integration allows AI models to utilize various web scraping and automation tools provided by Apify, facilitating tasks such as data extraction and web automation. -
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MATLAB Deep Learning Model Hub
Discover pretrained models for deep learning in MATLAB
Discover pre-trained models for deep learning in MATLAB. Pretrained image classification networks have already learned to extract powerful and informative features from natural images. Use them as a starting point to learn a new task using transfer learning. Inputs are RGB images, the output is the predicted label and score. -
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Hunyuan3D 2.0
High-Resolution 3D Assets Generation with Large Scale Diffusion Models
...Hunyuan3D-2 supports various enhancements and is available for deployment through tools like Blender and Hugging Face. Includes a user-friendly production/studio tool (Hunyuan3D-Studio) to manipulate/animate meshes. Condition-aligned shape generation via the DiT model, so generated mesh is influenced by input images or prompts. -
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SageMaker TensorFlow Training Toolkit
Toolkit for running TensorFlow training scripts on SageMaker
...A Batch Transform job runs an offline-inference job using your TensorFlow Serving model. Input data in S3 is converted to HTTP requests, and responses are saved to an output bucket in S3. -
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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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Qwen-Audio
Chat & pretrained large audio language model proposed by Alibaba Cloud
Qwen-Audio is a large audio-language model developed by Alibaba Cloud, built to accept various types of audio input (speech, natural sounds, music, singing) along with text input, and output text. There is also an instruction-tuned version called Qwen-Audio-Chat which supports conversational interaction (multi-round), audio + text input, creative tasks and reasoning over audio. -
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Template MCP Server
Template to quickly set up your own MCP server
The template-mcp-server is a TypeScript-based template designed to expedite the setup of Model Context Protocol (MCP) servers. It provides a basic server configuration with options for both standard input/output and HTTP transport using FastMCP. The template includes a structured framework for defining MCP tools, resources, and prompts, along with TypeScript configuration and development scripts. -
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LatentSync
Taming Stable Diffusion for Lip Sync
LatentSync is an open-source framework from ByteDance that produces high-quality lip-synchronization for video by using an audio-conditioned latent diffusion model, bypassing traditional intermediate motion representations. In effect, given a source video (with masked or reference frames) and an audio track, LatentSync directly generates frames whose lip motions and expressions align with the audio, producing convincing talking-head or animated lip-sync output. The system leverages a U-Net diffusion backbone, with cross-attention of audio embeddings (via an audio encoder) and reference video frames to guide generation, and applies a set of loss functions (temporal, perceptual, sync-net based) to enforce lip-sync accuracy, visual fidelity, and temporal consistency. ... -
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FLUX.2
Official inference repo for FLUX.2 models
FLUX.2 is a state-of-the-art open-weight image generation and editing model released by Black Forest Labs aimed at bridging the gap between research-grade capabilities and production-ready workflows. The model offers both text-to-image generation and powerful image editing, including editing of multiple reference images, with fidelity, consistency, and realism that push the limits of what open-source generative models have achieved. -
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AlphaFold 3
AlphaFold 3 inference pipeline
AlphaFold 3, developed by Google DeepMind, is an advanced deep learning system for predicting biomolecular structures and interactions with exceptional accuracy. This repository provides the complete inference pipeline for running AlphaFold 3, though access to the model parameters is restricted and must be obtained directly from Google under specific terms of use. The system is designed for scientific research applications in structural biology, biochemistry, and bioinformatics, enabling accurate modeling of proteins, ligands, and covalent modifications. Users can perform local predictions via Docker containers, integrating AlphaFold 3’s inference process with provided JSON input configurations. ... -
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SHAP
A game theoretic approach to explain the output of ml models
...To understand how a single feature effects the output of the model we can plot the SHAP value of that feature vs. the value of the feature for all the examples in a dataset. Since SHAP values represent a feature's responsibility for a change in the model output, the plot below represents the change in predicted house price as RM (the average number of rooms per house in an area) changes. -
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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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Step-Audio
Open-source framework for intelligent speech interaction
Step-Audio is a unified, open-source framework aimed at building intelligent speech systems that combine both comprehension and generation: it integrates large language models (LLMs) with speech input/output to handle not only semantic understanding but also rich vocal characteristics like tone, style, dialect, emotion, and prosody. The design moves beyond traditional separate-component pipelines (ASR → text model → TTS), instead offering a multimodal model that ingests speech or audio and produces speech accordingly, enabling natural dialogue, voice cloning, and expressive speech synthesis. ... -
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MCP Server and GW
An MCP stdio to HTTP SSE transport gateway with example server
mcp-server-and-gw is a Model Context Protocol (MCP) gateway that bridges standard input/output to HTTP Server-Sent Events (SSE) transport. It includes an example MCP server and client, facilitating the development and testing of MCP implementations. This tool is particularly useful for integrating MCP servers with applications like Claude Desktop that may not natively support remote server connections. -
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PersonaLive
Expressive Portrait Image Animation for Live Streaming
PersonaLive is an open-source diffusion-based portrait animation framework focused on generating expressive, long-duration animated sequences in real time, primarily for live streaming or interactive applications. It leverages deep generative models that condition on a static reference image and a driving input (such as motion or expression cues) to produce a seamless animated portrait sequence that can run indefinitely without segmentation artifacts. The framework prioritizes low-latency... -
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WhisperLive
A nearly-live implementation of OpenAI's Whisper
...It can handle microphone input, pre-recorded audio files, and network streams such as RTSP and HLS, making it flexible for live events, monitoring, or accessibility workflows. Configuration options let you control the number of clients, maximum connection time, and threading behavior so the server can be tuned for different deployment environments. On the client side, you can set the language, whether to translate into English, model size, voice activity detection, and output recording behavior. -
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CliWrap
Library for interacting with command-line interfaces
...It also includes flexible mechanisms for capturing standard output and error streams, enabling advanced automation scenarios. Overall, CliWrap simplifies process orchestration in .NET applications while maintaining strong safety and performance guarantees. -
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PersonaPlex
PersonaPlex code
...PersonaPlex also supports persona and voice control, allowing developers to define the role and speaking style of the agent using text prompts and voice conditioning, making it suitable for applications like customized voice assistants, interactive character agents, or domain-specific conversational tools. Internally, it processes continuous audio streams in a hybrid input format so that speech understanding and generation occur jointly. -
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DeepSeek-V3.2-Exp
An experimental version of DeepSeek model
DeepSeek-V3.2-Exp is an experimental release of the DeepSeek model family, intended as a stepping stone toward the next generation architecture. The key innovation in this version is DeepSeek Sparse Attention (DSA), a sparse attention mechanism that aims to optimize training and inference efficiency in long-context settings without degrading output quality. According to the authors, they aligned the training setup of V3.2-Exp with V3.1-Terminus so that benchmark results remain largely comparable, even though the internal attention mechanism changes. ...
