Showing 15 open source projects for "llama.cpp python"

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  • 1
    llama.cpp

    llama.cpp

    Port of Facebook's LLaMA model in C/C++

    The llama.cpp project enables the inference of Meta's LLaMA model (and other models) in pure C/C++ without requiring a Python runtime. It is designed for efficient and fast model execution, offering easy integration for applications needing LLM-based capabilities. The repository focuses on providing a highly optimized and portable implementation for running large language models directly within C/C++ environments.
    Downloads: 127 This Week
    Last Update:
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  • 2
    llama.cpp Python Bindings

    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.
    Downloads: 16 This Week
    Last Update:
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  • 3
    GPT4All

    GPT4All

    Run Local LLMs on Any Device. Open-source

    ...The software provides a simple, user-friendly application that can be downloaded and run on various platforms, including Windows, macOS, and Ubuntu, without requiring specialized hardware. It integrates with the llama.cpp implementation and supports multiple LLMs, allowing users to interact with AI models privately. This project also supports Python integrations for easy automation and customization. GPT4All is ideal for individuals and businesses seeking private, offline access to powerful LLMs.
    Downloads: 265 This Week
    Last Update:
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  • 4
    OuteTTS

    OuteTTS

    Interface for OuteTTS models

    ...It provides a high-level Interface API that wraps model configuration, speaker handling, and audio generation so you can focus on integrating speech into your application rather than wiring up low-level engines. The project supports multiple backends including llama.cpp (Python bindings and server), Hugging Face Transformers, ExLlamaV2, VLLM and a JavaScript interface via Transformers.js, allowing it to run on CPUs, NVIDIA CUDA GPUs, AMD ROCm, Vulkan-capable GPUs, and Apple Metal. It also includes a notion of speaker profiles: you can create a speaker from a short audio sample, save it as JSON, and reuse it for consistent voice identity across generations and sessions. ...
    Downloads: 0 This Week
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  • 5
    CoPaw

    CoPaw

    Your Personal AI Assistant; easy to install, deploy on local or coud

    CoPaw is a personal AI assistant designed to run on your own machine or in the cloud, giving you full control over memory, models, and data. Built by the AgentScope team, it connects to multiple chat platforms—including DingTalk, Feishu, QQ, Discord, iMessage, and more—through a single unified assistant. CoPaw supports both cloud-based LLM providers and fully local models such as llama.cpp, MLX, and Ollama, allowing you to operate without API keys if preferred. It includes a browser-based...
    Downloads: 30 This Week
    Last Update:
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  • 6
    llama2.c

    llama2.c

    Inference Llama 2 in one file of pure C

    llama2.c is a minimalist implementation of the Llama 2 language model architecture designed to run entirely in pure C. Created by Andrej Karpathy, this project offers an educational and lightweight framework for performing inference on small Llama 2 models without external dependencies. It provides a full training and inference pipeline: models can be trained in PyTorch and later executed using a concise 700-line C program (run.c). While it can technically load Meta’s official Llama 2...
    Downloads: 1 This Week
    Last Update:
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  • 7
    Backtrack Sampler

    Backtrack Sampler

    An easy-to-understand framework for LLM samplers

    Backtrack Sampler is a framework designed for experimenting with custom sampling strategies for language models (LLMs), enabling the ability to rewind and revise generated tokens. It allows developers to create and test their own token generation strategies by providing a base structure for manipulating logits and probabilities, making it a flexible tool for those interested in fine-tuning the behavior of LLMs.
    Downloads: 0 This Week
    Last Update:
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  • 8
    Qwen3

    Qwen3

    Qwen3 is the large language model series developed by Qwen team

    Qwen3 is a cutting-edge large language model (LLM) series developed by the Qwen team at Alibaba Cloud. The latest updated version, Qwen3-235B-A22B-Instruct-2507, features significant improvements in instruction-following, reasoning, knowledge coverage, and long-context understanding up to 256K tokens. It delivers higher quality and more helpful text generation across multiple languages and domains, including mathematics, coding, science, and tool usage. Various quantized versions,...
    Downloads: 60 This Week
    Last Update:
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  • 9
    Text Generation Web UI

    Text Generation Web UI

    Oobabooga - The definitive Web UI for local AI, with powerful features

    A gradio web UI for running Large Language Models like LLaMA, llama.cpp, GPT-J, Pythia, OPT, and GALACTICA. Dropdown menu for switching between models. Notebook mode that resembles OpenAI's playground. Chat mode for conversation and role playing. Instruct mode compatible with Alpaca and Open Assistant formats. Nice HTML output for GPT-4chan. Markdown output for GALACTICA, including LaTeX rendering. Custom chat characters. Advanced chat features (send images, get audio responses with TTS)....
    Downloads: 28 This Week
    Last Update:
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  • 10
    GPUStack

    GPUStack

    Performance-optimized AI inference on your GPUs

    GPUStack is an open-source GPU cluster management platform designed to simplify the deployment and operation of artificial intelligence models across heterogeneous hardware environments. The system aggregates GPU resources from multiple machines into a unified cluster so developers and administrators can run large language models and other AI workloads efficiently across distributed infrastructure. Instead of requiring complex orchestration systems such as Kubernetes, GPUStack provides a...
    Downloads: 13 This Week
    Last Update:
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  • 11
    Orpheus TTS

    Orpheus TTS

    Towards Human-Sounding Speech

    Orpheus TTS is a state-of-the-art open-source text-to-speech system built on a Llama-3B backbone, treating speech synthesis as a large language model problem instead of a traditional TTS pipeline. It is designed to produce human-like speech with natural intonation, emotion, and rhythm, targeting quality comparable to or better than many closed-source systems. The project ships both pretrained and finetuned English models, as well as a family of multilingual models released as a research...
    Downloads: 2 This Week
    Last Update:
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  • 12
    KoboldCpp

    KoboldCpp

    Run GGUF models easily with a UI or API. One File. Zero Install.

    KoboldCpp is an easy-to-use AI text-generation software for GGML and GGUF models, inspired by the original KoboldAI. It's a single self-contained distributable that builds off llama.cpp and adds many additional powerful features.
    Downloads: 325 This Week
    Last Update:
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  • 13
    llama2-webui

    llama2-webui

    Run any Llama 2 locally with gradio UI on GPU or CPU from anywhere

    Running Llama 2 with gradio web UI on GPU or CPU from anywhere (Linux/Windows/Mac).
    Downloads: 0 This Week
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  • 14
    Chinese-LLaMA-Alpaca-2 v2.0

    Chinese-LLaMA-Alpaca-2 v2.0

    Chinese LLaMA & Alpaca large language model + local CPU/GPU training

    This project has open-sourced the Chinese LLaMA model and the Alpaca large model with instruction fine-tuning to further promote the open research of large models in the Chinese NLP community. Based on the original LLaMA , these models expand the Chinese vocabulary and use Chinese data for secondary pre-training, which further improves the basic semantic understanding of Chinese. At the same time, the Chinese Alpaca model further uses Chinese instruction data for fine-tuning, which...
    Downloads: 0 This Week
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  • 15
    Mellum-4b-base

    Mellum-4b-base

    JetBrains’ 4B parameter code model for completions

    ...With a context window of 8,192 tokens, it excels at code completion, fill-in-the-middle tasks, and intelligent code suggestions for professional developer tools and IDEs. The model is efficient for both cloud inference with vLLM and local deployment using llama.cpp or Ollama, thanks to its bf16 precision and AMP training. While the base model is not fine-tuned for downstream tasks, it is designed to be easily adapted through supervised fine-tuning (SFT) or reinforcement learning (RL). Benchmarks on RepoBench, SAFIM, and HumanEval demonstrate its competitive performance, with specialized fine-tuned versions for Python already showing strong improvements.
    Downloads: 0 This Week
    Last Update:
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