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:
- 88882bf98014f076e0941d0fdfb4413ccadce5666fb8c4029b54bfa3f37360e4
- Size of remote file:
- 3.71 kB
- SHA256:
- e3a24b86dc8b34a882b77a31c8216d8667502cfb507e36d708d903c6cdc3cbaa
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