Instructions to use Sjdan/finetuning12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/finetuning12 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/finetuning12")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/finetuning12") model = AutoModelForCTC.from_pretrained("Sjdan/finetuning12", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/finetuning12: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/Sjdan/finetuning12/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/finetuning12/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/finetuning12/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 9a6847b0148a6c27e9d0ef49b7d0f0e9e6b9a4600a13c0aff251996783790dc6
- Size of remote file:
- 3.45 kB
- SHA256:
- f93a99f929e086623126c7928f5c6de9d0256dba1b0d2a3107ea9b3baeb23f82
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