Instructions to use SumitMdhr/Model_17.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SumitMdhr/Model_17.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SumitMdhr/Model_17.2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("SumitMdhr/Model_17.2") model = AutoModelForCTC.from_pretrained("SumitMdhr/Model_17.2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e9e449f4588d278f3322f68f55913fabdb07249908322ee83508237a7bd2b9f
- Size of remote file:
- 2.49 GB
- SHA256:
- 5458ae60896766afaaaf9bcee2f27df3bdd10f86999190f95c269974ebcf0ca9
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