Showing 10 open source projects for "tune"

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  • 1
    Google DeepMind GraphCast and GenCast

    Google DeepMind GraphCast and GenCast

    Global weather forecasting model using graph neural networks and JAX

    ...Both models are built on JAX and integrate advanced neural architectures capable of learning from multi-scale geophysical data represented on icosahedral meshes. The package includes pretrained model weights, normalization statistics, and demonstration notebooks that allow users to replicate and fine-tune weather forecasting experiments in Colab or on Google Cloud TPUs and GPUs.
    Downloads: 9 This Week
    Last Update:
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  • 2
    Step-Video-T2V

    Step-Video-T2V

    State-of-the-art (SoTA) text-to-video pre-trained model

    Step-Video-T2V is a state-of-the-art text-to-video foundation model developed to generate videos from natural-language prompts; its 30B-parameter architecture is designed to produce coherent, temporally extended video sequences — up to around 204 frames — based on input text. Under the hood it uses a compressed latent representation (a Video-VAE) to reduce spatial and temporal redundancy, and a denoising diffusion (or similar) process over that latent space to generate smooth, plausible...
    Downloads: 5 This Week
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  • 3
    4M

    4M

    4M: Massively Multimodal Masked Modeling

    ...The design leans into flexibility and steerability, so prompts and masks can shape behavior without bespoke heads per task. In short, 4M provides a unified recipe to pretrain large multimodal models that generalize broadly while remaining practical to fine-tune.
    Downloads: 0 This Week
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  • 4
    MetaCLIP

    MetaCLIP

    ICLR2024 Spotlight: curation/training code, metadata, distribution

    ...The repository provides training logic, adaptation strategies (e.g. prompt tuning, adapter modules), and evaluation across base and target domains to measure how well the model retains its general knowledge while specializing as needed. It includes utilities to fine-tune vision-language embeddings, compute prompt or adapter updates, and benchmark across transfer and retention metrics. MetaCLIP is especially suited for real-world settings where a model must continuously incorporate new visual categories or domains over time.
    Downloads: 0 This Week
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  • 5
    GLM-4.5V

    GLM-4.5V

    GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning

    GLM-4.5V is the preceding iteration in the GLM-V series that laid much of the groundwork for general multimodal reasoning and vision-language understanding. It embodies the design philosophy of mixing visual and textual modalities into a unified model capable of general-purpose reasoning, content understanding, and generation, while already supporting a wide variety of tasks: from image captioning and visual question answering to content recognition, GUI-based agents, video understanding,...
    Downloads: 1 This Week
    Last Update:
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  • 6
    Demucs

    Demucs

    Code for the paper Hybrid Spectrogram and Waveform Source Separation

    ...Demucs supports GPU-accelerated inference and can process multi-channel audio with chunked streaming for real-time or batch operation. It also provides training scripts and utilities to fine-tune on custom datasets, along with remixing and enhancement tools.
    Downloads: 53 This Week
    Last Update:
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  • 7
    FastViT

    FastViT

    This repository contains the official implementation of research

    ...Training and inference recipes highlight straightforward integration into common vision tasks such as classification, detection, and segmentation. The codebase provides reference implementations and checkpoints that make it easy to evaluate or fine-tune on downstream datasets. In practice, FastViT offers drop-in backbones that reduce compute and memory pressure without exotic training tricks.
    Downloads: 0 This Week
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  • 8
    Menagerie

    Menagerie

    A collection of high-quality models for the MuJoCo physics engine

    ...It serves as a comprehensive library of accurate and ready-to-use robotic, biomechanical, and mechanical models, ensuring users can perform reliable simulations without having to build or tune models from scratch. The repository aims to improve reproducibility and quality across robotics research by providing verified models that adhere to consistent design and physical standards. Each model directory contains its 3D assets, MJCF XML definitions, licensing information, and example scenes for visualization and testing. The collection spans a wide range of categories including robotic arms, humanoids, quadrupeds, mobile manipulators, drones, and biomechanical systems. ...
    Downloads: 5 This Week
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  • 9
    Video Pre-Training

    Video Pre-Training

    Learning to Act by Watching Unlabeled Online Videos

    The Video PreTraining (VPT) repository provides code and model artifacts for a project where agents learn to act by watching human gameplay videos—specifically, gameplay of Minecraft—using behavioral cloning. The idea is to learn general priors of control from large-scale, unlabeled video data, and then optionally fine-tune those priors for more goal-directed behavior via environment interaction. The repository contains demonstration models of different widths, fine-tuned variants (e.g. for building houses or early-game tasks), and inference scripts that instantiate agents from pretrained weights. Key modules include the behavioral cloning logic, the agent wrapper, and data loading pipelines (with an accessible skeleton for loading Minecraft demonstration data). ...
    Downloads: 0 This Week
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    eProcurement Software

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  • 10
    TimeSformer

    TimeSformer

    The official pytorch implementation of our paper

    ...Because the attention is global across frames, TimeSformer can reason about dependencies across long time spans, not just local neighborhoods. The official implementation in PyTorch provides configurations, pretrained models, and training scripts that make it straightforward to evaluate or fine-tune on video datasets. TimeSformer was influential in showing that pure transformer architectures—without convolutional backbones—can perform strongly on video classification tasks. Its flexible attention design allows experimenting with different factoring (spatial-then-temporal, joint, etc.) to trade off compute, memory, and accuracy.
    Downloads: 1 This Week
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