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:
- 057c0709a421d9ea84ff2418cc34f87af2f1ee398e5cb77f71b44c5d8905a039
- Size of remote file:
- 3.71 kB
- SHA256:
- cebe7a1e85037b2cc8a8eff570ccc426dd84ce5cd7894e73f8cb63f2195153a6
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