Showing 12 open source projects for "json-c"

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    Automate contact and company data extraction

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  • 1
    AlphaFold 3

    AlphaFold 3

    AlphaFold 3 inference pipeline

    ...The system is designed for scientific research applications in structural biology, biochemistry, and bioinformatics, enabling accurate modeling of proteins, ligands, and covalent modifications. Users can perform local predictions via Docker containers, integrating AlphaFold 3’s inference process with provided JSON input configurations. The software includes flexible options for running both data preprocessing and GPU-accelerated inference, allowing users to adapt to available computational resources.
    Downloads: 4 This Week
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  • 2
    Qwen-2.5-VL

    Qwen-2.5-VL

    Qwen2.5-VL is the multimodal large language model series

    ...Trained on a comprehensive dataset of up to 18 trillion tokens, Qwen2.5 models exhibit significant improvements in instruction following, long-text generation (exceeding 8,000 tokens), and structured data comprehension, such as tables and JSON formats. They support context lengths up to 128,000 tokens and offer multilingual capabilities in over 29 languages, including Chinese, English, French, Spanish, and more. The models are open-source under the Apache 2.0 license, with resources and documentation available on platforms like Hugging Face and ModelScope.
    Downloads: 12 This Week
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  • 3
    ChatGPT Retrieval Plugin

    ChatGPT Retrieval Plugin

    The ChatGPT Retrieval Plugin lets you easily find personal documents

    ...The repo provides code for ingestion pipelines (embedding documents), APIs for querying, local server components, and privacy / PII detection modules. It also contains plugin manifest files (OpenAPI spec, plugin JSON) so that the retrieval backend can be registered in a plugin ecosystem. Because retrieval is often needed to make LLMs “know what’s in your docs” without leaking everything, this plugin aims to be a secure, flexible building block for retrieval-augmented generation (RAG) systems.
    Downloads: 0 This Week
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  • 4
    HunyuanOCR

    HunyuanOCR

    OCR expert VLM powered by Hunyuan's native multimodal architecture

    HunyuanOCR is an open-source, end-to-end OCR (optical character recognition) Vision-Language Model (VLM) developed by Tencent‑Hunyuan. It’s designed to unify the entire OCR pipeline, detection, recognition, layout parsing, information extraction, translation, and even subtitle or structured output generation, into a single model inference instead of a cascade of separate tools. Despite being fairly lightweight (about 1 billion parameters), it delivers state-of-the-art performance across a...
    Downloads: 4 This Week
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    Leverage AI to Automate Medical Coding

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  • 5
    CodeGeeX

    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...
    Downloads: 7 This Week
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  • 6
    BitNet

    BitNet

    Inference framework for 1-bit LLMs

    BitNet (bitnet.cpp) is a high-performance inference framework designed to optimize the execution of 1-bit large language models, making them more efficient for edge devices and local deployment. The framework offers significant speedups and energy reductions, achieving up to 6.17x faster performance on x86 CPUs and 70% energy savings, allowing the running of models such as the BitNet b1.58 100B with impressive efficiency. With support for lossless inference and enhanced processing power,...
    Downloads: 11 This Week
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  • 7
    fairseq2

    fairseq2

    FAIR Sequence Modeling Toolkit 2

    fairseq2 is a modern, modular sequence modeling framework developed by Meta AI Research as a complete redesign of the original fairseq library. Built from the ground up for scalability, composability, and research flexibility, fairseq2 supports a broad range of language, speech, and multimodal content generation tasks, including instruction fine-tuning, reinforcement learning from human feedback (RLHF), and large-scale multilingual modeling. Unlike the original fairseq—which evolved into a...
    Downloads: 2 This Week
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  • 8
    Tencent-Hunyuan-Large

    Tencent-Hunyuan-Large

    Open-source large language model family from Tencent Hunyuan

    ...It aims to provide competitive capability with efficient deployment and inference. FP8 quantization support to reduce memory usage (~50%) while maintaining precision. High benchmarking performance on tasks like MMLU, MATH, CMMLU, C-Eval, etc.
    Downloads: 1 This Week
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  • 9
    MuJoCo MPC

    MuJoCo MPC

    Real-time behaviour synthesis with MuJoCo, using Predictive Control

    ...The system supports multi-shooting optimization, enabling precise motion planning across diverse domains like quadruped locomotion, humanoid tracking, and dexterous manipulation. In addition to its C++ core, MJPC includes an experimental Python API, enabling integration with custom models and MuJoCo tasks for flexible scripting and experimentation.
    Downloads: 0 This Week
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  • 10
    VMZ (Video Model Zoo)

    VMZ (Video Model Zoo)

    VMZ: Model Zoo for Video Modeling

    The codebase was designed to help researchers and practitioners quickly reproduce FAIR’s results and leverage robust pre-trained backbones for downstream tasks. It also integrates Gradient Blending, an audio-visual modeling method that fuses modalities effectively (available in the Caffe2 implementation). Although VMZ is now archived and no longer actively maintained, it remains a valuable reference for understanding early large-scale video model training, transfer learning, and multimodal...
    Downloads: 0 This Week
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  • 11
    xFormers

    xFormers

    Hackable and optimized Transformers building blocks

    ...One of its key goals is efficient attention: it supports dense, sparse, low-rank, and approximate attention mechanisms (e.g. FlashAttention, Linformer, Performer) via interchangeable modules. The library includes memory-efficient operator implementations in both Python and optimized C++/CUDA, ensuring that performance isn’t sacrificed for modularity. It also integrates with PyTorch seamlessly so you can drop in its blocks to existing models, replace default attention layers, or build new architectures from scratch. xformers includes training, deployment, and memory profiling tools.
    Downloads: 0 This Week
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  • 12
    DeepSDF

    DeepSDF

    Learning Continuous Signed Distance Functions for Shape Representation

    DeepSDF is a deep learning framework for continuous 3D shape representation using Signed Distance Functions (SDFs), as presented in the CVPR 2019 paper DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation by Park et al. The framework learns a continuous implicit function that maps 3D coordinates to their corresponding signed distances from object surfaces, allowing compact, high-fidelity shape modeling. Unlike traditional discrete voxel grids or meshes, DeepSDF...
    Downloads: 0 This Week
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