Instructions to use niclas/models_sv_7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use niclas/models_sv_7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="niclas/models_sv_7")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("niclas/models_sv_7") model = AutoModelForCTC.from_pretrained("niclas/models_sv_7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from niclas/models_sv_7: direct link, hf CLI and curl.
- Browser
- Download file 2.8 kB
-
https://huggingface.co/niclas/models_sv_7/resolve/main/training_args.bin
- Command line
-
hf download hf://niclas/models_sv_7/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/niclas/models_sv_7/resolve/main/training_args.bin
2.8 kB
- Xet hash:
- abe3b49ee5a0f90e1a268064ab54486467ac0a6d0877ece9a43ed58a7563920e
- Size of remote file:
- 2.8 kB
- SHA256:
- 528350758c4065d63054e0f49b9903d67af189dcdd1cc7711f9d25cd727ea6ab
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