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")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Kuray107/RATS_clean") model = AutoModelForCTC.from_pretrained("Kuray107/RATS_clean") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:0e7afef5791c9d5c02ee6eb040705fcfba7908087bef305555983a828d8a8987
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size 1261901420
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