Showing 4 open source projects for "speed"

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    SentenceTransformers

    SentenceTransformers

    Multilingual sentence & image embeddings with BERT

    ...Further, it is easy to fine-tune your own models. Our models are evaluated extensively and achieve state-of-the-art performance on various tasks. Further, the code is tuned to provide the highest possible speed.
    Downloads: 6 This Week
    Last Update:
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  • 2
    Point-E

    Point-E

    Point cloud diffusion for 3D model synthesis

    ...While it does not match the fine detail of some slower methods, the tradeoff in speed makes it practical for prototyping and interactive 3D generation. The repository includes inference scripts, utilities for converting point clouds to meshes (e.g. via signed distance function regression), sample notebooks, and weight checkpoints. It also provides documentation on limitations, usage instructions, and example outputs.
    Downloads: 1 This Week
    Last Update:
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  • 3
    Data augmentation

    Data augmentation

    List of useful data augmentation resources

    ...To create more images for example, we could zoom in and save a result, we could change the brightness of the image or rotate it. To get a bigger sound dataset we could try to raise or lower the pitch of the audio sample or slow down/speed up. Keypoints/landmarks Augmentation, usually done with image augmentation (rotation, reflection) or graph augmentation methods (node/edge dropping) Spectrograms/Melspectrograms, usually done with time series data augmentation (jittering, perturbing, warping) or image augmentation (random erasing)
    Downloads: 0 This Week
    Last Update:
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  • 4
    onnxt5

    onnxt5

    Summarization, translation, sentiment-analysis, text-generation, etc.

    Summarization, translation, sentiment analysis, text-generation and more at blazing speed using a T5 version implemented in ONNX. This package is still in the alpha stage, therefore some functionalities such as beam searches are still in development. The simplest way to get started for generation is to use the default pre-trained version of T5 on ONNX included in the package. Please note that the first time you call get_encoder_decoder_tokenizer, the models are being downloaded which might take a minute or two. ...
    Downloads: 0 This Week
    Last Update:
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