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UsefulSensors
/
moonshine-streaming-medium

Automatic Speech Recognition
Transformers
Safetensors
English
moonshine_streaming
Eval Results
Model card Files Files and versions
xet
Community
4

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

  • Libraries
  • Transformers

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

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="UsefulSensors/moonshine-streaming-medium")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("UsefulSensors/moonshine-streaming-medium", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
moonshine-streaming-medium
1.07 GB
Ctrl+K
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  • 3 contributors
History: 11 commits
petewarden's picture
petewarden
Added link to GitHub repo
57b8436 verified 3 months ago
  • .gitattributes
    1.52 kB
    initial commit 4 months ago
  • README.md
    6.42 kB
    Added link to GitHub repo 3 months ago
  • config.json
    1.74 kB
    Upload config.json 3 months ago
  • generation_config.json
    167 Bytes
    Upload folder using huggingface_hub 4 months ago
  • model.safetensors
    1.06 GB
    xet
    Upload model.safetensors 3 months ago
  • preprocessor_config.json
    195 Bytes
    Upload 6 files 3 months ago
  • processor_config.json
    159 Bytes
    Upload 6 files 3 months ago
  • special_tokens_map.json
    96 Bytes
    Upload 6 files 3 months ago
  • tokenizer.json
    1.68 MB
    Upload 6 files 3 months ago
  • tokenizer_config.json
    172 Bytes
    Upload 6 files 3 months ago