Instructions to use hts98/Model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hts98/Model2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hts98/Model2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hts98/Model2") model = AutoModelForSpeechSeq2Seq.from_pretrained("hts98/Model2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c3adaf8b5751cb83cf363ae74d68f80dabc63469d3978da9e68175a91686d33
- Size of remote file:
- 3.06 GB
- SHA256:
- ebebb7380c550748af9a1bb4fd9e6b5f1d8c68e517a53239ac886c12ad922cc6
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