Instructions to use juierror/whisper-base-thai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use juierror/whisper-base-thai with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="juierror/whisper-base-thai")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("juierror/whisper-base-thai") model = AutoModelForSpeechSeq2Seq.from_pretrained("juierror/whisper-base-thai") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a24cc113de36046fb4e8aa21a86e86192162bcab8d59edaffbe5f7e900d010e
- Size of remote file:
- 290 MB
- SHA256:
- e8ab6beb1abc4995fe73181da21e6f521792c4174082cd126bb3db4f30556a56
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