Instructions to use Kuray107/RATS_clean with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kuray107/RATS_clean with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Kuray107/RATS_clean")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Kuray107/RATS_clean") model = AutoModelForCTC.from_pretrained("Kuray107/RATS_clean", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Kuray107/RATS_clean: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/Kuray107/RATS_clean/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Kuray107/RATS_clean/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Kuray107/RATS_clean/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- c97152cd7fca6644749e48debadb4fb62cc88a4b4536c8086a66a08cae253e0d
- Size of remote file:
- 1.26 GB
- SHA256:
- f03262987baa0c4970aacadf93d74dc8e784472c0b8aed480caa8bab5377fcd8
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