Instructions to use SumitMdhr/fASR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SumitMdhr/fASR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SumitMdhr/fASR")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("SumitMdhr/fASR") model = AutoModelForCTC.from_pretrained("SumitMdhr/fASR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 932f42b2b38f9b50030e7ffe5e238bd590704aae24ad13c77fa140c5ce5a4046
- Size of remote file:
- 1.26 GB
- SHA256:
- 4de0fead0f5ce6c67987b9bfc9b65241023781ccb3e21f9fec483716bb56cbe2
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