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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")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("smcleod/ibm-granite-speech-4.1-2b-nar-onnx", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
ibm-granite-speech-4.1-2b-nar-onnx / int8
2.48 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
smcleod's picture
smcleod
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34d82a9 verified 2 months ago
  • editor.onnx
    6.42 MB
    xet
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  • editor.onnx_data
    1.63 GB
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  • embed_tokens.onnx
    991 Bytes
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  • embed_tokens.onnx_data
    206 MB
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  • encoder.onnx
    3.39 MB
    xet
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  • encoder.onnx_data
    632 MB
    xet
    Add files using upload-large-folder tool 2 months ago