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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7d871b6d1ca458475dcd1a98f869f67011769928a31a858e30fd1c385155174
- Size of remote file:
- 3.06 GB
- SHA256:
- 7aac2fb628c8f7a78748c03d78d339e01ba3072c42086f65fe205e7eb21e8f32
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