Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Thai
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use biodatlab/whisper-th-large-combined with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use biodatlab/whisper-th-large-combined with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="biodatlab/whisper-th-large-combined")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("biodatlab/whisper-th-large-combined") model = AutoModelForSpeechSeq2Seq.from_pretrained("biodatlab/whisper-th-large-combined", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a545302d62606f9eb47fb426e5d3fa257b89dad90305132875fb3e6404f914d7
- Size of remote file:
- 6.17 GB
- SHA256:
- 05886d38fa219e31daf77cac80d299af8f06abf6c5361db791644dbfc3f41ead
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