Instructions to use jadasdn/open-ai-small-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jadasdn/open-ai-small-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jadasdn/open-ai-small-1", device_map="auto")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("jadasdn/open-ai-small-1") model = AutoModelForSpeechSeq2Seq.from_pretrained("jadasdn/open-ai-small-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 852962e12649219f534655cda491f17ebf75a50e04b1f7e63bb9cc67875e8fb8
- Size of remote file:
- 4.73 kB
- SHA256:
- 5a7c681f87dca5265b786322c50083dc4ebce5d6efc5fb98777c00c6a1e99fd7
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