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:
- f6f9a8d8423657ab58d4af852b649a0818bb45c4882583bb952f4c9bec9547ec
- Size of remote file:
- 151 MB
- SHA256:
- 1824317b480670ceab5447ca149bc3aa4505321e2958591ca9782004c3381315
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