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:
- c1906250bcec723bc356ad8dbec9f141f5cfb51eb67ca5a869dde2c99f4eeb4d
- Size of remote file:
- 4.54 kB
- SHA256:
- 04e749cc368d40262715f98a285422c6a1587c327180f8b716fbb6f03901007b
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