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EphAsad
/
SatellaSTT-27M

Automatic Speech Recognition
Transformers
ONNX
Safetensors
English
moonshine
science
microbiology
laboratory
Model card Files Files and versions
xet
Community

Instructions to use EphAsad/SatellaSTT-27M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use EphAsad/SatellaSTT-27M with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="EphAsad/SatellaSTT-27M")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("EphAsad/SatellaSTT-27M")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("EphAsad/SatellaSTT-27M", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
SatellaSTT-27M / benchmarks
9.87 kB
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  • 1 contributor
History: 2 commits
EphAsad's picture
EphAsad
Add ONNX equivalence and CPU benchmarks
45b4acf verified 2 days ago
  • evaluation_comparison.json
    1.18 kB
    Release SatellaSTT-27M PyTorch model with evaluation and CPU/GPU benchmarks 2 days ago
  • onnx_benchmarks.json
    7.8 kB
    Add ONNX equivalence and CPU benchmarks 2 days ago
  • pytorch_benchmarks.json
    891 Bytes
    Release SatellaSTT-27M PyTorch model with evaluation and CPU/GPU benchmarks 2 days ago