Automatic Speech Recognition
Transformers
ONNX
English
onnxruntime
speech
asr
granite
ibm
quantized
int8
fp16
Instructions to use smcleod/ibm-granite-speech-4.1-2b-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-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-onnx")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("smcleod/ibm-granite-speech-4.1-2b-onnx", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- abfb7cbb9586ad9fb4242931b7cef1d46ce251d8a021f219200211c4b392eda8
- Size of remote file:
- 913 kB
- SHA256:
- efe873c6d19468eda93d1751ba14615508e763312cac6112029914acec0f33a9
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