Instructions to use Sjdan/msl_dummy1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/msl_dummy1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/msl_dummy1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/msl_dummy1") model = AutoModelForCTC.from_pretrained("Sjdan/msl_dummy1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/msl_dummy1: direct link, hf CLI and curl.
- Browser
- Download file 3 kB
-
https://huggingface.co/Sjdan/msl_dummy1/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/msl_dummy1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/msl_dummy1/resolve/main/training_args.bin
3 kB
- Xet hash:
- b61ff6c62f1434ddd5a5f4759a8947930b0c1f2e943de51157bb944d4821d594
- Size of remote file:
- 3 kB
- SHA256:
- 65aed037f396b6dac670d6cd7a95cd3d6b8340287e00a12231e239d18c65c8ba
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