Showing 734 open source projects for "python programming language"

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  • 1
    PrivateGPT

    PrivateGPT

    Interact with your documents using the power of GPT

    PrivateGPT is a production-ready, privacy-first AI system that allows querying of uploaded documents using LLMs, operating completely offline in your own environment. It provides contextual generative AI capabilities without sending data externally. Now maintained under Zylon.ai with enterprise deployment options (air gapped, cloud, or on-prem).
    Downloads: 9 This Week
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  • 2
    Vanna

    Vanna

    Chat with your SQL database

    Vanna.AI is an AI-powered tool for natural language database querying, enabling users to interact with databases using simple English queries. It converts natural language questions into SQL queries, making data access more intuitive for non-technical users.
    Downloads: 2 This Week
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  • 3
    BudouX

    BudouX

    Standalone, small, language-neutral

    Standalone. Small. Language-neutral. BudouX is the successor to Budou, the machine learning-powered line break organizer tool. It is standalone. It works with no dependency on third-party word segmenters such as Google cloud natural language API. It is small. It takes only around 15 KB including its machine learning model. It's reasonable to use it even on the client-side. It is language-neutral. You can train a model for any language by feeding a dataset to BudouX’s training...
    Downloads: 0 This Week
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  • 4
    NeMo Curator

    NeMo Curator

    Scalable data pre processing and curation toolkit for LLMs

    NeMo Curator is a Python library specifically designed for fast and scalable dataset preparation and curation for large language model (LLM) use-cases such as foundation model pretraining, domain-adaptive pretraining (DAPT), supervised fine-tuning (SFT) and paramter-efficient fine-tuning (PEFT). It greatly accelerates data curation by leveraging GPUs with Dask and RAPIDS, resulting in significant time savings.
    Downloads: 0 This Week
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  • 5
    Kaleidoscope-SDK

    Kaleidoscope-SDK

    User toolkit for analyzing and interfacing with Large Language Models

    kaleidoscope-sdk is a Python module used to interact with large language models hosted via the Kaleidoscope service available at: https://github.com/VectorInstitute/kaleidoscope. It provides a simple interface to launch LLMs on an HPC cluster, asking them to perform basic features like text generation, but also retrieve intermediate information from inside the model, such as log probabilities and activations.
    Downloads: 0 This Week
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  • 6
    Phi-3-MLX

    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.
    Downloads: 0 This Week
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  • 7
    LangChain.js

    LangChain.js

    Building applications with LLMs through composability

    ...This is built to integrate as seamlessly as possible with the LangChain Python package. Specifically, this means all objects (prompts, LLMs, chains, etc) are designed in a way where they can be serialized and shared between languages.
    Downloads: 5 This Week
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  • 8
    MindNLP

    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.
    Downloads: 0 This Week
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  • 9
    Chonkie

    Chonkie

    The no-nonsense RAG chunking library

    Chonkie is an AI-powered framework designed for building conversational agents and chatbots with natural language understanding and multi-turn conversation support.
    Downloads: 0 This Week
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  • 10
    TPOT

    TPOT

    A Python Automated Machine Learning tool that optimizes ML

    Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
    Downloads: 0 This Week
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  • 11
    DeepSeek R1

    DeepSeek R1

    Open-source, high-performance AI model with advanced reasoning

    DeepSeek-R1 is an open-source large language model developed by DeepSeek, designed to excel in complex reasoning tasks across domains such as mathematics, coding, and language. DeepSeek R1 offers unrestricted access for both commercial and academic use. The model employs a Mixture of Experts (MoE) architecture, comprising 671 billion total parameters with 37 billion active parameters per token, and supports a context length of up to 128,000 tokens. DeepSeek-R1's training regimen uniquely...
    Downloads: 61 This Week
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  • 12
    DataDreamer

    DataDreamer

    DataDreamer: Prompt. Generate Synthetic Data. Train & Align Models

    DataDreamer is a tool designed to assist in the generation and manipulation of synthetic data for various applications, including testing and machine learning.
    Downloads: 2 This Week
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  • 13
    LLMs-from-scratch

    LLMs-from-scratch

    Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

    LLMs-from-scratch is an educational codebase that walks through implementing modern large-language-model components step by step. It emphasizes building blocks—tokenization, embeddings, attention, feed-forward layers, normalization, and training loops—so learners understand not just how to use a model but how it works internally. The repository favors clear Python and NumPy or PyTorch implementations that can be run and modified without heavyweight frameworks obscuring the logic. ...
    Downloads: 2 This Week
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  • 14
    Gemma

    Gemma

    Gemma open-weight LLM library, from Google DeepMind

    Gemma, developed by Google DeepMind, is a family of open-weights large language models (LLMs) built upon the research and technology behind Gemini. This repository provides the official implementation of the Gemma PyPI package, a JAX-based library that enables users to load, interact with, and fine-tune Gemma models. The framework supports both text and multi-modal input, allowing natural language conversations that incorporate visual content such as images. It includes APIs for...
    Downloads: 1 This Week
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  • 15
    LLM Action

    LLM Action

    Technical principles related to large models

    LLM-Action is a knowledge/tutorial/repository that shares principles, techniques, and real-world experience related to large language models (LLMs), focusing on LLM engineering, deployment, optimization, inference, compression, and tooling. It organizes content in domains like training, inference, compression, alignment, evaluation, pipelines, and applications. Sections covering infrastructure, engineering, and deployment. Repository templates, sample code, and resource links. Articles/code...
    Downloads: 2 This Week
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  • 16
    Chronos Forecasting

    Chronos Forecasting

    Pretrained (Language) Models for Probabilistic Time Series Forecasting

    Chronos is a family of pretrained time series forecasting models based on language model architectures. A time series is transformed into a sequence of tokens via scaling and quantization, and a language model is trained on these tokens using the cross-entropy loss. Once trained, probabilistic forecasts are obtained by sampling multiple future trajectories given the historical context. Chronos models have been trained on a large corpus of publicly available time series data, as well as...
    Downloads: 2 This Week
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  • 17
    GPT4Free

    GPT4Free

    The official gpt4free repository

    gpt4free is an open-source project offering free, unrestricted access to GPT‑4–style language models without requiring an API key. The repository includes scripts and server implementations designed to replicate OpenAI’s GPT‑4 API behavior by leveraging publicly available or self-hosted models. It’s licensed under GPL‑v3.
    Downloads: 6 This Week
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  • 18
    Keras Hub

    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.
    Downloads: 6 This Week
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  • 19
    MLX-Audio

    MLX-Audio

    A text-to-speech, speech-to-text and speech-to-speech library

    ...Because it uses MLX and targets Apple Silicon, inference is fast and can take advantage of hardware acceleration and quantization for efficient on-device performance. The project provides a straightforward CLI (mlx_audio.tts.generate) as well as a Python API for programmatic generation of audio, including parameters for voice choice, speed, language hints, output format, and sample rate. It includes examples such as audiobook generation to demonstrate long-form synthesis and joined audio segments. On top of that, MLX-Audio offers a modern web interface powered by FastAPI, with real-time waveform and 3D visualizations, file upload, and audio management.
    Downloads: 3 This Week
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  • 20
    GPT-2

    GPT-2

    Code for the paper Language Models are Unsupervised Multitask Learners

    This repository contains the code and model weights for GPT-2, a large-scale unsupervised language model described in the OpenAI paper “Language Models are Unsupervised Multitask Learners.” The intent is to provide a starting point for researchers and engineers to experiment with GPT-2: generate text, fine‐tune on custom datasets, explore model behavior, or study its internal phenomena. The repository includes scripts for sampling, training, downloading pre-trained models, and utilities for...
    Downloads: 5 This Week
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  • 21
    MiniMind

    MiniMind

    Train a 26M-parameter GPT from scratch in just 2h

    minimind is a framework that enables users to train a 26-million-parameter GPT (Generative Pre-trained Transformer) model from scratch in approximately two hours. It provides a streamlined process for data preparation, model training, and evaluation, making it accessible for individuals and organizations to develop their own language models without extensive computational resources.
    Downloads: 1 This Week
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  • 22
    rwkv.cpp

    rwkv.cpp

    INT4/INT5/INT8 and FP16 inference on CPU for RWKV language model

    Besides the usual FP32, it supports FP16, quantized INT4, INT5 and INT8 inference. This project is focused on CPU, but cuBLAS is also supported. RWKV is a novel large language model architecture, with the largest model in the family having 14B parameters. In contrast to Transformer with O(n^2) attention, RWKV requires only state from the previous step to calculate logits. This makes RWKV very CPU-friendly on large context lengths.
    Downloads: 1 This Week
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  • 23
    EvaDB

    EvaDB

    Database system for building simpler and faster AI-powered application

    ...This programming complexity prevents people who are experts in other domains from benefiting from these models. Running these deep learning models on large document or video datasets is costly and time-consuming. For example, the state-of-the-art object detection model takes multiple GPU years to process just a week’s videos from a single traffic monitoring camera.
    Downloads: 1 This Week
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  • 24
    MarkItDown

    MarkItDown

    Python tool for converting files and office documents to Markdown

    MarkItDown is a lightweight Python utility developed by Microsoft for converting various files and office documents to Markdown format. It is particularly useful for preparing documents for use with large language models and related text analysis pipelines. ​
    Downloads: 2 This Week
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  • 25
    DOLMA

    DOLMA

    Data and tools for generating and inspecting OLMo pre-training data

    DOLMA (Data Optimization and Learning for Model Alignment) is a framework designed to manage large-scale datasets for training and fine-tuning language models efficiently.
    Downloads: 0 This Week
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