55 programs for "raspberry-gpio-python" with 2 filters applied:

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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: 83 This Week
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  • 2
    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: 40 This Week
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  • 3
    DeepSeek-V3

    DeepSeek-V3

    Powerful AI language model (MoE) optimized for efficiency/performance

    DeepSeek-V3 is a robust Mixture-of-Experts (MoE) language model developed by DeepSeek, featuring a total of 671 billion parameters, with 37 billion activated per token. It employs Multi-head Latent Attention (MLA) and the DeepSeekMoE architecture to enhance computational efficiency. The model introduces an auxiliary-loss-free load balancing strategy and a multi-token prediction training objective to boost performance. Trained on 14.8 trillion diverse, high-quality tokens, DeepSeek-V3...
    Downloads: 35 This Week
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  • 4
    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: 20 This Week
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  • 5
    GPT-NeoX

    GPT-NeoX

    Implementation of model parallel autoregressive transformers on GPUs

    This repository records EleutherAI's library for training large-scale language models on GPUs. Our current framework is based on NVIDIA's Megatron Language Model and has been augmented with techniques from DeepSpeed as well as some novel optimizations. We aim to make this repo a centralized and accessible place to gather techniques for training large-scale autoregressive language models, and accelerate research into large-scale training. For those looking for a TPU-centric codebase, we...
    Downloads: 1 This Week
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  • 6
    Stable Diffusion

    Stable Diffusion

    High-Resolution Image Synthesis with Latent Diffusion Models

    Stable Diffusion Version 2. The Stable Diffusion project, developed by Stability AI, is a cutting-edge image synthesis model that utilizes latent diffusion techniques for high-resolution image generation. It offers an advanced method of generating images based on text input, making it highly flexible for various creative applications. The repository contains pretrained models, various checkpoints, and tools to facilitate image generation tasks, such as fine-tuning and modifying the models....
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    Downloads: 70 This Week
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  • 7
    FinGPT

    FinGPT

    Open-Source Financial Large Language Models!

    FinGPT is an open-source large language model tailored specifically for financial tasks. Developed by AI4Finance Foundation, it is designed to assist with various financial applications, such as forecasting, financial sentiment analysis, and portfolio management. FinGPT has been trained on a diverse range of financial datasets, making it a powerful tool for finance professionals looking to leverage AI for data-driven decision-making. The model is freely available on platforms like Hugging...
    Downloads: 31 This Week
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  • 8
    Qwen

    Qwen

    Qwen (通义千问) chat/pretrained large language model Alibaba Cloud

    Qwen is a series of large language models developed by Alibaba Cloud, consisting of various pretrained versions like Qwen-1.8B, Qwen-7B, Qwen-14B, and Qwen-72B. These models, which range from smaller to larger configurations, are designed for a wide range of natural language processing tasks. They are openly available for research and commercial use, with Qwen's code and model weights shared on GitHub. Qwen's capabilities include text generation, comprehension, and conversation, making it a...
    Downloads: 31 This Week
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  • 9
    Hunyuan3D 2.0

    Hunyuan3D 2.0

    High-Resolution 3D Assets Generation with Large Scale Diffusion Models

    The Hunyuan3D-2 model, developed by Tencent, is designed for generating high-resolution 3D assets using large-scale diffusion models. This model offers advanced capabilities for creating detailed 3D models, including texture enhancements, multi-view shape generation, and rapid inference for real-time applications. It is particularly useful for industries requiring high-quality 3D content, such as gaming, film, and virtual reality. Hunyuan3D-2 supports various enhancements and is available...
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    Downloads: 24 This Week
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  • 10
    DiffRhythm

    DiffRhythm

    Di♪♪Rhythm: Blazingly Fast & Simple End-to-End Song Generation

    DiffRhythm is an open-source, diffusion-based model designed to generate full-length songs. Focused on music creation, it combines advanced AI techniques to produce coherent and creative audio compositions. The model utilizes a latent diffusion architecture, making it capable of producing high-quality, long-form music. It can be accessed on Huggingface, where users can interact with a demo or download the model for further use. DiffRhythm offers tools for both training and inference, and its...
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    Downloads: 20 This Week
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  • 11
    Grok-1

    Grok-1

    Open-source, high-performance Mixture-of-Experts large language model

    Grok-1 is a 314-billion-parameter Mixture-of-Experts (MoE) large language model developed by xAI. Designed to optimize computational efficiency, it activates only 25% of its weights for each input token. In March 2024, xAI released Grok-1's model weights and architecture under the Apache 2.0 license, making them openly accessible to developers. The accompanying GitHub repository provides JAX example code for loading and running the model. Due to its substantial size, utilizing Grok-1...
    Downloads: 13 This Week
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  • 12
    Qwen2.5-Coder

    Qwen2.5-Coder

    Qwen2.5-Coder is the code version of Qwen2.5, the large language model

    Qwen2.5-Coder, developed by QwenLM, is an advanced open-source code generation model designed for developers seeking powerful and diverse coding capabilities. It includes multiple model sizes—ranging from 0.5B to 32B parameters—providing solutions for a wide array of coding needs. The model supports over 92 programming languages and offers exceptional performance in generating code, debugging, and mathematical problem-solving. Qwen2.5-Coder, with its long context length of 128K tokens, is...
    Downloads: 8 This Week
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  • 13
    CSM (Conversational Speech Model)

    CSM (Conversational Speech Model)

    A Conversational Speech Generation Model

    The CSM (Conversational Speech Model) is a speech generation model developed by Sesame AI that creates RVQ audio codes from text and audio inputs. It uses a Llama backbone and a smaller audio decoder to produce audio codes for realistic speech synthesis. The model has been fine-tuned for interactive voice demos and is hosted on platforms like Hugging Face for testing. CSM offers a flexible setup and is compatible with CUDA-enabled GPUs for efficient execution.
    Downloads: 5 This Week
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  • 14
    GLM-4-32B-0414

    GLM-4-32B-0414

    Open Multilingual Multimodal Chat LMs

    GLM-4-32B-0414 is a powerful open-source large language model featuring 32 billion parameters, designed to deliver performance comparable to leading models like OpenAI’s GPT series. It supports multilingual and multimodal chat capabilities with an extensive 32K token context length, making it ideal for dialogue, reasoning, and complex task completion. The model is pre-trained on 15 trillion tokens of high-quality data, including substantial synthetic reasoning datasets, and further enhanced...
    Downloads: 3 This Week
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  • 15
    Janus-Pro

    Janus-Pro

    Janus-Series: Unified Multimodal Understanding and Generation Models

    Janus is a cutting-edge, unified multimodal model designed to advance both multimodal understanding and generation. It features a decoupled visual encoding approach that allows it to handle visual tasks separately from the generative tasks, resulting in enhanced flexibility and performance. With a singular transformer architecture, Janus outperforms previous models by surpassing specialized task-specific models in its ability to handle diverse multimodal inputs and generate high-quality...
    Downloads: 2 This Week
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  • 16
    ChatGLM2-6B

    ChatGLM2-6B

    An Open Bilingual Chat LLM | Open Source Bilingual Conversation LLM

    ChatGLM2-6B is an advanced open-source bilingual dialogue model developed by THUDM. It is the second iteration of the ChatGLM series, designed to offer enhanced performance while maintaining the strengths of its predecessor, including smooth conversation flow and low deployment barriers. The model is fine-tuned for both Chinese and English languages, making it a versatile tool for various multilingual applications. ChatGLM2-6B aims to push the boundaries of natural language understanding and...
    Downloads: 1 This Week
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  • 17
    Dia-1.6B

    Dia-1.6B

    Dia-1.6B generates lifelike English dialogue and vocal expressions

    ... on enterprise GPUs, though CPU and quantized versions are planned. The format supports [S1]/[S2] tags to differentiate speakers and integrates easily into Python workflows. While not tuned to a specific voice, user-provided audio can guide output style. Licensed under Apache 2.0, Dia is intended for research and educational use, with explicit restrictions on misuse like identity mimicry or deceptive content.
    Downloads: 0 This Week
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  • 18
    grok-1

    grok-1

    Grok-1 is a 314B-parameter open-weight language model by xAI

    Grok-1 is a large-scale language model released by xAI, featuring 314 billion parameters and made available under the Apache 2.0 license. It is designed for text generation and was trained for advanced language understanding and reasoning capabilities. Grok-1 is currently distributed as open weights, with inference support requiring multi-GPU hardware due to its size. The model can be downloaded from Hugging Face and run using the accompanying Python code in the official GitHub repository...
    Downloads: 0 This Week
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  • 19
    ERNIE-4.5-300B-A47B-FP8-Paddle

    ERNIE-4.5-300B-A47B-FP8-Paddle

    ERNIE 4.5 MoE model in FP8 for efficient high-performance inference

    .... It is especially well-suited for production environments requiring high throughput and lower memory use, while maintaining high reasoning and generation quality. The model can be used with FastDeploy and integrates cleanly with Python APIs for prompt-based generation workflows. It supports long context lengths (up to 131,072 tokens) and includes both Chinese and English prompt templates for web search applications.
    Downloads: 0 This Week
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  • 20
    starcoder

    starcoder

    Code generation model trained on 80+ languages with FIM support

    StarCoder is a 15.5B parameter language model developed by BigCode for code generation tasks across more than 80 programming languages. It is trained on 1 trillion tokens from the permissively licensed dataset The Stack v1.2, using the Fill-in-the-Middle (FIM) objective and Multi-Query Attention to enhance performance. With an extended context window of 8192 tokens and pretraining in bfloat16, StarCoder can generate, complete, or refactor code in various languages, with English as the...
    Downloads: 0 This Week
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  • 21
    DeepSWE-Preview

    DeepSWE-Preview

    State-of-the-art RL-trained coding agent for complex SWE tasks

    DeepSWE-Preview is a 32.8B parameter open-source coding agent trained solely with reinforcement learning (RL) to perform complex software engineering (SWE) tasks. Built on top of Qwen3-32B, it achieves 59% accuracy on the SWE-Bench-Verified benchmark—currently the highest among open-weight models. The model navigates and edits large codebases using tools like a file editor, bash execution, and search, within the R2E-Gym environment. Its training emphasizes sparse reward signals, test-time...
    Downloads: 0 This Week
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  • 22
    mms-300m-1130-forced-aligner

    mms-300m-1130-forced-aligner

    CTC-based forced aligner for audio-text in 158 languages

    ... to the TorchAudio forced alignment API. Users can integrate it easily through the Python package ctc-forced-aligner, and it supports GPU acceleration via PyTorch. The alignment pipeline includes audio processing, emission generation, tokenization, and span detection, making it suitable for speech analysis, transcription syncing, and dataset creation. This model is especially useful for researchers and developers working with low-resource languages or building multilingual speech systems.
    Downloads: 0 This Week
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  • 23
    yolo-world-mirror

    yolo-world-mirror

    Mirror of Ultralytics YOLO-World model weights for object detection

    ... descriptions. These weights are compatible with Ultralytics’ tooling and documentation, making it easier for developers to deploy or fine-tune the model. The mirror allows users to work with YOLO-World models through a centralized platform without downloading from alternate sources. It enables flexible integration with Ultralytics’ Python API or CLI tools for real-time and high-performance object detection tasks.
    Downloads: 0 This Week
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  • 24
    segmentation-3.0

    segmentation-3.0

    Speaker segmentation model for 10s audio chunks with powerset labels

    segmentation-3.0 is a voice activity and speaker segmentation model from the pyannote.audio framework, designed to analyze 10-second mono audio sampled at 16kHz. It outputs a (num_frames, num_classes) matrix using a powerset encoding that includes non-speech, individual speakers, and overlapping speech for up to three speakers. Trained with pyannote.audio 3.0.0 on a rich blend of datasets—including AISHELL, DIHARD, VoxConverse, and more—it enables downstream tasks like voice activity...
    Downloads: 0 This Week
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  • 25
    MiniMax-M1

    MiniMax-M1

    Open-weight, large-scale hybrid-attention reasoning model

    MiniMax-M1 is the world’s first open-weight, large-scale hybrid-attention reasoning model designed for long-context and complex reasoning tasks. Powered by a hybrid Mixture-of-Experts (MoE) architecture combined with a lightning attention mechanism, it efficiently supports context lengths up to 1 million tokens—eight times larger than many contemporary models. MiniMax-M1 significantly reduces computational overhead at generation time, consuming only about 25% FLOPs compared to comparable...
    Downloads: 0 This Week
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