Instructions to use Sjdan/m14_main with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/m14_main with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/m14_main")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/m14_main") model = AutoModelForCTC.from_pretrained("Sjdan/m14_main", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/m14_main: direct link, hf CLI and curl.
- Browser
- Download file 3 kB
-
https://huggingface.co/Sjdan/m14_main/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/m14_main/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/m14_main/resolve/main/training_args.bin
3 kB
- Xet hash:
- 697aaae1538939dbe37bd8e799cf0c91fed6558fd6b2b16f414dcad95ef80921
- Size of remote file:
- 3 kB
- SHA256:
- 450cefc6b924ba42126e01ee2fe2f21c363a7d52d47412e1778bd12b9c3f66c9
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