Instructions to use tensorops/whisper-small-th with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorops/whisper-small-th with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="tensorops/whisper-small-th")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("tensorops/whisper-small-th") model = AutoModelForSpeechSeq2Seq.from_pretrained("tensorops/whisper-small-th", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15ef368053058733bfab136e66345948acdb94523b7b3320fe3db3e2b6817b17
- Size of remote file:
- 3.52 kB
- SHA256:
- 32cbdaf0c7633999be2f881c94497d94e8cf3f0468c1b9685c425df7f2adf709
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