Instructions to use ffedox/dataset-en-whisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ffedox/dataset-en-whisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ffedox/dataset-en-whisper")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ffedox/dataset-en-whisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("ffedox/dataset-en-whisper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc646963b3baaf0fcc403cb4a3697f88845036963f4e7829b59abbdd3f970ab2
- Size of remote file:
- 4.92 kB
- SHA256:
- 446b790bd498acb9c9a6149aa26e244abfebf2fe27bdf269dc787143abc78a1f
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