Instructions to use niclas/models_sv_6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use niclas/models_sv_6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="niclas/models_sv_6")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("niclas/models_sv_6") model = AutoModelForCTC.from_pretrained("niclas/models_sv_6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from niclas/models_sv_6: direct link, hf CLI and curl.
- Browser
- Download file 2.8 kB
-
https://huggingface.co/niclas/models_sv_6/resolve/main/training_args.bin
- Command line
-
hf download hf://niclas/models_sv_6/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/niclas/models_sv_6/resolve/main/training_args.bin
2.8 kB
- Xet hash:
- bc99d2a08e21a803c780985311a829091a9e86d13111461f07376a8f9e36732c
- Size of remote file:
- 2.8 kB
- SHA256:
- 0a2d20ec58718d69ae2fb6ecfde1f1719b20bf1ef351b8d995b91b29073731b1
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