Instructions to use jadasdn/open-ai-small-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jadasdn/open-ai-small-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jadasdn/open-ai-small-4")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("jadasdn/open-ai-small-4") model = AutoModelForSpeechSeq2Seq.from_pretrained("jadasdn/open-ai-small-4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1dca2efa85ebbedc00049bb2068ba394d4e93885885af7b2405f92b9bfb15dd9
- Size of remote file:
- 4.73 kB
- SHA256:
- 5cfb3529fb0d59ba55bf1b9b2969b1a81727ac226935d1b093db66889d9a7115
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