Instructions to use hts98/test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hts98/test1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hts98/test1")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hts98/test1") model = AutoModelForSpeechSeq2Seq.from_pretrained("hts98/test1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba7fdb4e9ce398878030bbd5bf053fc9f297dc1dd4e3834a9382e551a5a75131
- Size of remote file:
- 3.57 kB
- SHA256:
- 088f7053f8c9c136bafd8c314f2eadb7fc82a7b624da7e43a92cbbe003b5c60e
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