Transformers.js

Run 🤗 Transformers in your browser!

Demo

Play around with some of these models:

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    Notes:
    • Clicking Generate for the first time will download the corresponding model from the HuggingFace Hub. All subsequent requests will use the cached model.
    • For more information about the different parameters, check out HuggingFace's guide to text generation.

    Quick tour

    Installation
    To install via NPM, run:
    npm i @xenova/transformers
    Alternatively, you can use it in vanilla JS, without any bundler, by using a CDN or static hosting. For example, using ES Modules, you can import the library with:
    <script type="module">
        import { pipeline } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers';
    </script>
    Basic example
    It's super easy to translate from existing code!
    from transformers import pipeline
    
    # Allocate a pipeline for sentiment-analysis
    pipe = pipeline('sentiment-analysis')
    
    out = pipe('I love transformers!')
    # [{'label': 'POSITIVE', 'score': 0.999806941}]

    Python (original)

    import { pipeline } from '@xenova/transformers';
    
    // Allocate a pipeline for sentiment-analysis
    let pipe = await pipeline('sentiment-analysis');
    
    let out = await pipe('I love transformers!');
    // [{'label': 'POSITIVE', 'score': 0.999817686}]

    JavaScript (ours)


    In the same way as the Python library, you can use a different model by providing its name as the second argument to the pipeline function. For example:
    // Use a different model for sentiment-analysis
    let pipe = await pipeline('sentiment-analysis', 'nlptown/bert-base-multilingual-uncased-sentiment');

    For the full list of available tasks and architectures, check out the documentation.