Instructions to use luigisaetta/whisper-atco2-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use luigisaetta/whisper-atco2-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="luigisaetta/whisper-atco2-large")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("luigisaetta/whisper-atco2-large") model = AutoModelForSpeechSeq2Seq.from_pretrained("luigisaetta/whisper-atco2-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f68719ad0e6380ae2ca181c97a78159ccae3402c0552b3956bd460486708b57
- Size of remote file:
- 6.17 GB
- SHA256:
- ebaa48dac8004d6b82d780786b73db19bdd65e032156868f43214999e18104a4
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