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smcleod
/
ibm-granite-speech-4.1-2b-nar-onnx

Automatic Speech Recognition
Transformers
ONNX
English
onnxruntime
speech
asr
granite
ibm
quantized
int8
fp16
non-autoregressive
nar
Model card Files Files and versions
xet
Community

Instructions to use smcleod/ibm-granite-speech-4.1-2b-nar-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use smcleod/ibm-granite-speech-4.1-2b-nar-onnx with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="smcleod/ibm-granite-speech-4.1-2b-nar-onnx")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("smcleod/ibm-granite-speech-4.1-2b-nar-onnx", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
ibm-granite-speech-4.1-2b-nar-onnx / test_fixtures
2.49 MB
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  • 1 contributor
History: 1 commit
smcleod's picture
smcleod
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34d82a9 verified 6 months ago
  • README.md
    2.25 kB
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  • expected_attention_mask.npy
    6.87 kB
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  • expected_audio_embeds.npy
    1.4 MB
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  • expected_input_features.npy
    540 kB
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  • sample_audio.wav
    540 kB
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  • test_fixture.json
    1.06 kB
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