Search Results for "compiler python linux" - Page 15
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Showing 1697 open source projects for "compiler python linux"
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VectorizedMultiAgentSimulator (VMAS)
VMAS is a vectorized differentiable simulator
VectorizedMultiAgentSimulator is a high-performance, vectorized simulator for multi-agent systems, focusing on large-scale agent interactions in shared environments. It is designed for research in multi-agent reinforcement learning, robotics, and autonomous systems where thousands of agents need to be simulated efficiently. -
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Open Interface
Control Any Computer Using LLMs
Open Interface is a cross-platform application that allows users to control their computers using large language models (LLMs). By sending user requests to an LLM backend, it determines the necessary steps and executes them by simulating keyboard and mouse inputs. The system can adjust its actions based on real-time feedback, providing a self-driving computer experience. -
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Llama Cookbook
Solve end to end problems using Llama model family
The Llama Cookbook is the official Meta LLaMA guide for inference, fine‑tuning, RAG, and multi-step use-cases. It offers recipes, code samples, and integration examples across provider platforms (WhatsApp, SQL, long context workflows), enabling developers to quickly harness LLaMA models -
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Keras Hub
Pretrained model hub for Keras 3
Keras Hub is a repository of pre-trained models for Keras 3, offering a collection of ready-to-use models for various machine-learning tasks. KerasHub is an extension of the core Keras API; KerasHub components are provided as Layer and Model implementations. If you are familiar with Keras, congratulations. You already understand most of KerasHub. -
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SetFit
Efficient few-shot learning with Sentence Transformers
SetFit is an efficient and prompt-free framework for few-shot fine-tuning of Sentence Transformers. It achieves high accuracy with little labeled data - for instance, with only 8 labeled examples per class on the Customer Reviews sentiment dataset, SetFit is competitive with fine-tuning RoBERTa Large on the full training set of 3k examples. -
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Hummingbird
Hummingbird compiles trained ML models into tensor computation
Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to seamlessly leverage neural network frameworks (such as PyTorch) to accelerate traditional ML models. Thanks to Hummingbird, users can benefit from (1) all the current and future optimizations implemented in neural network frameworks; (2) native hardware acceleration; (3) having a unique platform to support both traditional and neural network models; and having all of... -
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Dream Textures
Stable Diffusion built-in to Blender
Create textures, concept art, background assets, and more with a simple text prompt. Use the 'Seamless' option to create textures that tile perfectly with no visible seam. Texture entire scenes with 'Project Dream Texture' and depth to image. Re-style animations with the Cycles render pass. Run the models on your machine to iterate without slowdowns from a service. Create textures, concept art, and more with text prompts. Learn how to use the various configuration options to get exactly what... -
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NVIDIA NeMo
Toolkit for conversational AI
NVIDIA NeMo, part of the NVIDIA AI platform, is a toolkit for building new state-of-the-art conversational AI models. NeMo has separate collections for Automatic Speech Recognition (ASR), Natural Language Processing (NLP), and Text-to-Speech (TTS) models. Each collection consists of prebuilt modules that include everything needed to train on your data. Every module can easily be customized, extended, and composed to create new conversational AI model architectures. Conversational AI... -
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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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MCP Text Editor
Provides line-oriented text file editing capabilities
The MCP Text Editor Server provides line-oriented text file editing capabilities through a standardized API, optimized for integration with Large Language Models (LLMs). It enables efficient partial file access, minimizing token usage while ensuring safe concurrent editing. -
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Obsei
Obsei is a low code AI powered automation tool
Obsei is an automated no-code/low-code AI-powered text observation and analysis framework, designed for extracting insights from unstructured text data such as social media, reviews, and logs. -
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FastRAG
Efficient Retrieval Augmentation and Generation Framework
fastRAG is a research framework for efficient and optimized retrieval augmented generative pipelines, incorporating state-of-the-art LLMs and Information Retrieval. fastRAG is designed to empower researchers and developers with a comprehensive tool set for advancing retrieval augmented generation. -
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Data-Juicer
Data processing for and with foundation models
Data-Juicer is an open-source data processing and augmentation framework designed to enhance the quality and diversity of datasets for machine learning tasks. It includes a modular pipeline for scalable data transformation. -
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mcpo
A simple, secure MCP-to-OpenAPI proxy server
mcpo is a minimal bridge that exposes any MCP tool as an OpenAPI-compatible HTTP server. Instead of writing glue code, you point mcpo at an MCP server command and it generates REST endpoints and an OpenAPI spec that other systems (or LLM agent frameworks) can call immediately. This design lets you reuse a growing library of MCP servers with platforms that only understand HTTP+OpenAPI, unifying tool access across ecosystems. The project emphasizes “dead-simple” setup and pairs with Open WebUI... -
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firerpa LAMDA
The most powerful Android RPA agent framework
lamda is an Android RPA agent framework that provides visual remote desktop control and automation at scale, geared toward testing, automation validation, and device management. It exposes a clean UI to monitor and interact with connected devices and includes tooling to script actions reliably across apps and OS versions. The project emphasizes low-friction setup and powerful control primitives so teams can move from interactive validation to repeatable automation. A public wiki, releases,... -
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MaxKB
Open-source platform for building enterprise-grade agents
MaxKB (Max Knowledge Brain) is an open-source platform for building enterprise-grade AI agents with strong knowledge retrieval, RAG pipelines, and workflow orchestration. It focuses on practical deployments such as customer support, internal knowledge bases, research assistants, and education, bundling tools for data ingestion, chunking, embedding, retrieval, and answer synthesis. The system exposes flexible tool-use (including MCP), supports multi-model backends, and provides dashboards for... -
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AReal
Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible
AReaL is an open source, fully asynchronous reinforcement learning training system. AReal is designed for large reasoning and agentic models. It works with models that perform reasoning over multiple steps, agents interacting with environments. It is developed by the AReaL Team at Ant Group (inclusionAI) and builds upon the ReaLHF project. Release of training details, datasets, and models for reproducibility. It is intended to facilitate reproducible RL training on reasoning / agentic tasks,... -
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ChatGLM-6B
ChatGLM-6B: An Open Bilingual Dialogue Language Model
ChatGLM-6B is an open bilingual (Chinese + English) conversational language model based on the GLM architecture, with approximately 6.2 billion parameters. The project provides inference code, demos (command line, web, API), quantization support for lower memory deployment, and tools for finetuning (e.g., via P-Tuning v2). It is optimized for dialogue and question answering with a balance between performance and deployability in consumer hardware settings. Support for quantized inference... -
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Agent S2
Agent S: an open agentic framework that uses computers like a human
Simular's Agent S2 represents a leap forward in the development of computer-use agents, capable of autonomously interacting with a range of devices and interfaces. By integrating specialized AI models, Agent S2 delivers state-of-the-art performance, whether on desktop systems or smartphones. Through modular architecture, it efficiently handles complex tasks, such as navigating UIs, performing low-level actions like text selection, and executing high-level strategies like planning.... -
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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... -
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KServe
Standardized Serverless ML Inference Platform on Kubernetes
KServe provides a Kubernetes Custom Resource Definition for serving machine learning (ML) models on arbitrary frameworks. It aims to solve production model serving use cases by providing performant, high abstraction interfaces for common ML frameworks like Tensorflow, XGBoost, ScikitLearn, PyTorch, and ONNX. It encapsulates the complexity of autoscaling, networking, health checking, and server configuration to bring cutting edge serving features like GPU Autoscaling, Scale to Zero, and... -
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MMDeploy
OpenMMLab Model Deployment Framework
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN... -
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Hivemind
Decentralized deep learning in PyTorch. Built to train models
Hivemind is a PyTorch library for decentralized deep learning across the Internet. Its intended usage is training one large model on hundreds of computers from different universities, companies, and volunteers. Distributed training without a master node: Distributed Hash Table allows connecting computers in a decentralized network. Fault-tolerant backpropagation: forward and backward passes succeed even if some nodes are unresponsive or take too long to respond. Decentralized parameter... -
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Logfire MCP
The Logfire MCP Server is here
The Logfire MCP Server is a Model Context Protocol server that allows AI applications to access OpenTelemetry traces and metrics sent to Logfire. It enables retrieval and analysis of telemetry data, enhancing debugging and observability workflows. -
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Universal Tool Calling Protocol (UTCP)
Official python implementation of UTCP. UTCP is an open standard
The python-utcp repository is the official Python SDK implementation of the Universal Tool Calling Protocol (UTCP). UTCP is an open, modern standard designed to let AI agents call any tool or API directly—over HTTP, CLI, WebSocket, gRPC, and more—without the overhead of extra wrapper layers or middleware. It leverages a modular, plugin-based architecture built around Pydantic models and separates the core functionality into a lightweight client and extensible protocol plugins, enabling...
