Instructions to use maratos/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maratos/checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="maratos/checkpoints")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("maratos/checkpoints") model = AutoModelForSpeechSeq2Seq.from_pretrained("maratos/checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff949cf7505462e40a67d044c7cc901f8eae87131242d9823dca940832156b95
- Size of remote file:
- 7.48 kB
- SHA256:
- f12c42cf7f21fef4bb33200e4db1e6c41df13229f2f9f8e85c0d0aaed9e024e7
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