Showing 10 open source projects for "python samples"

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  • 1
    DeepVariant

    DeepVariant

    DeepVariant is an analysis pipeline that uses a deep neural networks

    ... extends DeepVariant's functionality, allowing it to utilize the power of neural networks to predict genomic variants in trios or duos. See this page for more details and instructions on how to run DeepTrio. Out-of-the-box use for PCR-positive samples and low quality sequencing runs, and easy adjustments for different sequencing technologies and non-human species.
    Downloads: 0 This Week
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  • 2
    Llama Cookbook

    Llama Cookbook

    Solve end to end problems using Llama model family

    The Llama Cookbook is the official Meta LLaMA guide for inference, fine‑tuning, RAG, and multi-step use-cases. It offers recipes, code samples, and integration examples across provider platforms (WhatsApp, SQL, long context workflows), enabling developers to quickly harness LLaMA models
    Downloads: 0 This Week
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  • 3
    Denoising Diffusion Probabilistic Model

    Denoising Diffusion Probabilistic Model

    Implementation of Denoising Diffusion Probabilistic Model in Pytorch

    Implementation of Denoising Diffusion Probabilistic Model in Pytorch. It is a new approach to generative modeling that may have the potential to rival GANs. It uses denoising score matching to estimate the gradient of the data distribution, followed by Langevin sampling to sample from the true distribution. If you simply want to pass in a folder name and the desired image dimensions, you can use the Trainer class to easily train a model.
    Downloads: 0 This Week
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  • 4
    Lightly

    Lightly

    A python library for self-supervised learning on images

    A python library for self-supervised learning on images. We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training...
    Downloads: 0 This Week
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  • 5
    TensorFlow Documentation

    TensorFlow Documentation

    TensorFlow documentation

    An end-to-end platform for machine learning. TensorFlow makes it easy to create ML models that can run in any environment. Learn how to use the intuitive APIs through interactive code samples.
    Downloads: 3 This Week
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  • 6
    FID score for PyTorch

    FID score for PyTorch

    Compute FID scores with PyTorch

    This is a port of the official implementation of Fréchet Inception Distance to PyTorch. FID is a measure of similarity between two datasets of images. It was shown to correlate well with human judgement of visual quality and is most often used to evaluate the quality of samples of Generative Adversarial Networks. FID is calculated by computing the Fréchet distance between two Gaussians fitted to feature representations of the Inception network. The weights and the model are exactly the same...
    Downloads: 2 This Week
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  • 7
    CakeChat

    CakeChat

    CakeChat: Emotional Generative Dialog System

    CakeChat is a backend for chatbots that are able to express emotions via conversations. The code is flexible and allows to condition model's responses by an arbitrary categorical variable. For example, you can train your own persona-based neural conversational model or create an emotional chatting machine. Hierarchical Recurrent Encoder-Decoder (HRED) architecture for handling deep dialog context. Multilayer RNN with GRU cells. The first layer of the utterance-level encoder is always...
    Downloads: 0 This Week
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  • 8
    Deepvoice3_pytorch

    Deepvoice3_pytorch

    PyTorch implementation of convolutional neural networks

    An open source implementation of Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning.
    Downloads: 0 This Week
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  • 9

    Training Image Operators from Samples

    Tools to train Image Operators automatically from a set of samples.

    TRIOS - Training Image Operators from Samples is a set of tools to bring Image Processing closer to scientists in general. It is capable of estimating an operator between two images using only pairs of samples that contain an input image and the desired output. The operator is saved to a file and can be applied to any image.
    Downloads: 0 This Week
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    Photo and Video Editing APIs and SDKs

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  • 10
    This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
    Downloads: 0 This Week
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