Instructions to use hts98/Model1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hts98/Model1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hts98/Model1")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hts98/Model1") model = AutoModelForSpeechSeq2Seq.from_pretrained("hts98/Model1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91c7063eaa1ced8a96c138dd931862d0d20950150fd56192f9438ced15ead762
- Size of remote file:
- 3.06 GB
- SHA256:
- 5da75f0201e989badaa9061ba9da97d6e590492a5115adbdf37994bd9ce823cd
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