Instructions to use manifoldix/att1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manifoldix/att1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="manifoldix/att1")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("manifoldix/att1") model = AutoModelForSpeechSeq2Seq.from_pretrained("manifoldix/att1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b25791e841f4cefdb488ca762d0924ddf9cbe1f7fdabfb47b9f5cb26bfa92bd
- Size of remote file:
- 6.17 GB
- SHA256:
- 69d2691bccbfa0cdda0e327627c4078cafab4b7626131fa37872ae9e273aba79
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