Showing 2 open source projects for "cpu-z"

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    Tokenizers

    Tokenizers

    Fast State-of-the-Art Tokenizers optimized for Research and Production

    ...Train new vocabularies and tokenize, using today’s most used tokenizers. Extremely fast (both training and tokenization), thanks to the Rust implementation. Takes less than 20 seconds to tokenize a GB of text on a server’s CPU. Easy to use, but also extremely versatile. Designed for both research and production. Full alignment tracking. Even with destructive normalization, it’s always possible to get the part of the original sentence that corresponds to any token. Does all the pre-processing: Truncation, Padding, add the special tokens your model needs.
    Downloads: 3 This Week
    Last Update:
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  • 2
    shimmy

    shimmy

    Python-free Rust inference server

    ...It supports modern model formats such as GGUF and SafeTensors and can automatically discover models stored locally or in common directories used by other AI tools. Advanced capabilities include CPU offloading for Mixture-of-Experts models and GPU acceleration, enabling large models to run on consumer hardware with limited VRAM.
    Downloads: 2 This Week
    Last Update:
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