Instructions to use jadasdn/open-ai-small-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jadasdn/open-ai-small-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jadasdn/open-ai-small-3")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("jadasdn/open-ai-small-3") model = AutoModelForSpeechSeq2Seq.from_pretrained("jadasdn/open-ai-small-3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 400cec0e70aa0e805d28a50a31a5ff7127bc8cd6fdd96319658859fa217c2c57
- Size of remote file:
- 4.73 kB
- SHA256:
- 67f64c4df171c22a798ab9368303ddc1280d83d96a197533cb91952d4509a310
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