Instructions to use hts98/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hts98/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hts98/model")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hts98/model") model = AutoModelForSpeechSeq2Seq.from_pretrained("hts98/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f386763a063fe68a78a390203809fda69b29fcd98198c5993f1dc9c2842ea8ec
- Size of remote file:
- 3.06 GB
- SHA256:
- 73fbb9c4814bbb4ec3621003978b535f8374f56c111aa0e76595d1d1143511a5
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