Instructions to use thak123/gom-stt-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thak123/gom-stt-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="thak123/gom-stt-v3")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("thak123/gom-stt-v3") model = AutoModelForSpeechSeq2Seq.from_pretrained("thak123/gom-stt-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 251f58b3d4182f6ab108e19e7d8c483cf7a57b554de4c7ef86ee4ce25bb6232b
- Size of remote file:
- 967 MB
- SHA256:
- ec2cabdd38979e61d3d055080727e03a5ad43e2d82de26580ddb1a5f9e0665fb
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