Instructions to use thak123/whisper-small-gom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thak123/whisper-small-gom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="thak123/whisper-small-gom")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("thak123/whisper-small-gom") model = AutoModelForSpeechSeq2Seq.from_pretrained("thak123/whisper-small-gom", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from thak123/whisper-small-gom: direct link, hf CLI and curl.
- Browser
- Download file 3.77 kB
-
https://huggingface.co/thak123/whisper-small-gom/resolve/main/training_args.bin
- Command line
-
hf download hf://thak123/whisper-small-gom/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/thak123/whisper-small-gom/resolve/main/training_args.bin
3.77 kB
- Xet hash:
- 9173fbe329f6a662a55cd247ad6063c09d60acd6d94537ebe7d6f5db319cc8c2
- Size of remote file:
- 3.77 kB
- SHA256:
- 27d0542ecab23674b7c03434081710f0fb270c142a842031984047ea9c793cf7
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