Search Results for "artificial intelligence linux" - Page 5
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Showing 2973 open source projects for "artificial intelligence linux"
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DocTR
Library for OCR-related tasks powered by Deep Learning
DocTR provides an easy and powerful way to extract valuable information from your documents. Seemlessly process documents for Natural Language Understanding tasks: we provide OCR predictors to parse textual information (localize and identify each word) from your documents. Robust 2-stage (detection + recognition) OCR predictors with pretrained parameters. User-friendly, 3 lines of code to load a document and extract text with a predictor. State-of-the-art performances on public document... -
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nanobot
🐈 nanobot: The Ultra-Lightweight Clawdbot / OpenClaw
nanobot is an ultra-lightweight personal AI assistant designed to deliver powerful agent capabilities without unnecessary complexity. Built in just ~4,000 lines of clean, readable code, it offers a minimalist alternative to heavyweight agent frameworks while retaining core intelligence and extensibility. nanobot is optimized for speed and efficiency, enabling fast startup times and low resource usage across environments. Its research-ready architecture makes it easy for developers to... -
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ACE-Step 1.5
The most powerful local music generation model
ACE-Step 1.5 is an advanced open-source foundation model for AI-driven music generation that pushes beyond traditional limitations in speed, musical coherence, and controllability by innovating in architecture and training design. It integrates cutting-edge generative techniques—such as diffusion-based synthesis combined with compressed autoencoders and lightweight transformer elements—to produce high-quality full-length music tracks with rapid inference times, capable of generating a... -
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TrustGraph
Deploy reasoning AI agents powered by agentic graph RAG in minutes
TrustGraph is an AI-driven framework designed to assess and visualize trust relationships within networks, aiding in the analysis of trustworthiness and influence among entities. -
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huggingface_hub
The official Python client for the Huggingface Hub
The huggingface_hub library allows you to interact with the Hugging Face Hub, a platform democratizing open-source Machine Learning for creators and collaborators. Discover pre-trained models and datasets for your projects or play with the thousands of machine-learning apps hosted on the Hub. You can also create and share your own models, datasets, and demos with the community. The huggingface_hub library provides a simple way to do all these things with Python. -
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FLUX.1
Official inference repo for FLUX.1 models
FLUX.1 repository contains inference code and tooling for the FLUX.1 text-to-image diffusion models, enabling developers and researchers to generate and edit images from natural-language prompts using open-weight versions of the model on their own hardware or within custom applications. The project is part of a larger family of FLUX models developed by Black Forest Labs, designed to produce high-quality, detailed visuals from text descriptions with competitive prompt adherence and artistic... -
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Cybergod
A program that can do anything to earn money without human operators
AGI Computer Control is an experimental autonomous software system designed to operate independently and generate income without human intervention. It aims to simulate artificial general intelligence (AGI) by leveraging evolutionary algorithms, deep active inference, and other advanced AI techniques. The project explores the boundaries of machine autonomy and self-directed behavior in computational environments. -
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RSS to Telegram Bot
A Telegram RSS bot that cares about your reading experience
A Telegram RSS bot that cares about your reading experience. -
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Scanpy
Single-cell analysis in Python
Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It includes preprocessing, visualization, clustering, trajectory inference and differential expression testing. The Python-based implementation efficiently deals with datasets of more than one million cells. -
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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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MindNLP
Easy-to-use and high-performance NLP and LLM framework
MindNLP is a natural language processing library built on the MindSpore framework, providing tools and models for various NLP tasks. -
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llama.cpp Python Bindings
Python bindings for llama.cpp
llama-cpp-python provides Python bindings for llama.cpp, enabling the integration of LLaMA (Large Language Model Meta AI) language models into Python applications. This facilitates the use of LLaMA's capabilities in natural language processing tasks within Python environments. -
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Text Generation Inference
Large Language Model Text Generation Inference
Text Generation Inference is a high-performance inference server for text generation models, optimized for Hugging Face's Transformers. It is designed to serve large language models efficiently with optimizations for performance and scalability. -
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Pyreft
ReFT: Representation Finetuning for Language Models
PyreFT is a tool by Stanford NLP for fine-tuning transformer models with an emphasis on efficient, resource-conserving training and customizability for NLP tasks. -
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AudioLM - Pytorch
Implementation of AudioLM audio generation model in Pytorch
Implementation of AudioLM, a Language Modeling Approach to Audio Generation out of Google Research, in Pytorch It also extends the work for conditioning with classifier free guidance with T5. This allows for one to do text-to-audio or TTS, not offered in the paper. Yes, this means VALL-E can be trained from this repository. It is essentially the same. This repository now also contains a MIT licensed version of SoundStream. It is also compatible with EnCodec, however, be aware that it... -
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Zettelkasten MCP
Implements the Zettelkasten knowledge management methodology
The Zettelkasten MCP Server is a Model Context Protocol (MCP) server that implements the Zettelkasten knowledge management methodology. It allows users to create, link, and manage notes, facilitating a structured and interconnected note-taking system. -
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Director
AI video agents framework for next-gen video interactions
Director is a video database management system designed to organize, search, and retrieve large collections of video content efficiently. -
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DSPy
DSPy: The framework for programming—not prompting—language models
Developed by the Stanford NLP Group, DSPy (Declarative Self-improving Python) is a framework that enables developers to program language models through compositional Python code rather than relying solely on prompt engineering. It facilitates the construction of modular AI systems and provides algorithms for optimizing prompts and weights, enhancing the quality and reliability of language model outputs. -
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LangCheck
Simple, Pythonic building blocks to evaluate LLM applications
Simple, Pythonic building blocks to evaluate LLM applications. -
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deepface
A Lightweight Face Recognition and Facial Attribute Analysis
DeepFace is a lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for python. It is a hybrid face recognition framework wrapping state-of-the-art models: VGG-Face, FaceNet, OpenFace, DeepFace, DeepID, ArcFace, Dlib, SFace and GhostFaceNet. Experiments show that human beings have 97.53% accuracy on facial recognition tasks whereas those models already reached and passed that accuracy level. -
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Jittor
Jittor is a high-performance deep learning framework
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators. The whole framework and meta-operators are compiled just in time. A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement... -
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HanLP
Han Language Processing
HanLP is a multilingual Natural Language Processing (NLP) library composed of a series of models and algorithms. Built on TensorFlow 2.0, it was designed to advance state-of-the-art deep learning techniques and popularize the application of natural language processing in both academia and industry. HanLP is capable of lexical analysis (Chinese word segmentation, part-of-speech tagging, named entity recognition), syntax analysis, text classification, and sentiment analysis. It comes with... -
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MOSS-TTS-Nano
MOSS-TTS-Nano is an open-source multilingual tiny speech generation
MOSS-TTS-Nano is a lightweight text-to-speech model designed for real-time voice generation in resource-constrained environments. It is part of the broader MOSS-TTS family and focuses on delivering high-quality speech synthesis with a compact architecture. The model operates efficiently on CPU-only systems, enabling deployment without specialized hardware. It supports multilingual voice cloning and produces high-fidelity audio with low latency. The system uses an autoregressive audio... -
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Qwen3-TTS
Qwen3-TTS is an open-source series of TTS models
Qwen3-TTS is an open-source text-to-speech (TTS) project built around the Qwen3 large language model family, focused on generating high-quality, natural-sounding speech from plain text input. It provides researchers and developers with tools to transform text into expressive, intelligible audio, supporting multiple languages and voice characteristics tuned for clarity and fluidity. The project includes pre-trained models and inference scripts that let users synthesize speech locally or... -
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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.
