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
Download training_args.bin from thak123/gom-stt-v3: direct link, hf CLI and curl.
- Browser
- Download file 4.16 kB
-
https://huggingface.co/thak123/gom-stt-v3/resolve/main/training_args.bin
- Command line
-
hf download hf://thak123/gom-stt-v3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/thak123/gom-stt-v3/resolve/main/training_args.bin
4.16 kB
- Xet hash:
- c2f8fe894fe18aaad4707dfc47ac309c5e8f96088d7a7c3a8a7556251f9f8311
- Size of remote file:
- 4.16 kB
- SHA256:
- a4e9a3b27c683427c69bdf882bbb3b956b231cbb38fef1809b467093b8abbd68
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