Instructions to use Sjdan/msl_dummy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/msl_dummy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/msl_dummy")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/msl_dummy") model = AutoModelForCTC.from_pretrained("Sjdan/msl_dummy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/msl_dummy: direct link, hf CLI and curl.
- Browser
- Download file 3 kB
-
https://huggingface.co/Sjdan/msl_dummy/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/msl_dummy/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/msl_dummy/resolve/main/training_args.bin
3 kB
- Xet hash:
- c9eb6d902f71b5d04f19ae3604ffb84b7fb6a192403c5f34ee7ebba15c391f1a
- Size of remote file:
- 3 kB
- SHA256:
- 48de66d9d7ddbca4d0da90c4e80c910bd0c91455990169ae3b101cafcdc5572b
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