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:
- 03ebd41542370f787100751f4598e4844eea107255307659a2b28dc9f74f51d6
- Size of remote file:
- 3.58 kB
- SHA256:
- 2100c1cbcabeb8fb7bca484c0473e6b3dc7074403e3c4cc104a18d7112290927
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