Instructions to use tensorops/whisper-th-small-combined with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorops/whisper-th-small-combined with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="tensorops/whisper-th-small-combined")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("tensorops/whisper-th-small-combined") model = AutoModelForSpeechSeq2Seq.from_pretrained("tensorops/whisper-th-small-combined", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88dba70a6395cd632f923e6a20489d4e45ab2e7b7c58df907a249df2c97ce43c
- Size of remote file:
- 4.35 kB
- SHA256:
- 92e0d28a477d6fbed86250bc2bdb7420c074fb1d27d9be486675bd887280e570
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