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eustlb
/
moonshine-streaming-medium

Automatic Speech Recognition
Transformers
Safetensors
moonshine_streaming
Model card Files Files and versions
xet
Community

Instructions to use eustlb/moonshine-streaming-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use eustlb/moonshine-streaming-medium with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="eustlb/moonshine-streaming-medium")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("eustlb/moonshine-streaming-medium")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("eustlb/moonshine-streaming-medium")
  • Notebooks
  • Google Colab
  • Kaggle
moonshine-streaming-medium
1.07 GB
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  • 1 contributor
History: 3 commits
eustlb's picture
eustlb HF Staff
Upload processor
428b29e verified 3 months ago
  • .gitattributes
    1.52 kB
    initial commit 3 months ago
  • README.md
    5.17 kB
    Upload MoonshineStreamingForConditionalGeneration 3 months ago
  • config.json
    1.76 kB
    Upload MoonshineStreamingForConditionalGeneration 3 months ago
  • generation_config.json
    136 Bytes
    Upload MoonshineStreamingForConditionalGeneration 3 months ago
  • model.safetensors
    1.06 GB
    xet
    Upload MoonshineStreamingForConditionalGeneration 3 months ago
  • processor_config.json
    310 Bytes
    Upload processor 3 months ago
  • tokenizer.json
    3.76 MB
    Upload processor 3 months ago
  • tokenizer_config.json
    200 Bytes
    Upload processor 3 months ago