Instructions to use jadasdn/open-ai-small-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jadasdn/open-ai-small-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jadasdn/open-ai-small-2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("jadasdn/open-ai-small-2") model = AutoModelForSpeechSeq2Seq.from_pretrained("jadasdn/open-ai-small-2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d9eeaf5f2bc9c3f7e8a5b51429056eb8066d50a63c4f6a7dc56188da8c65369
- Size of remote file:
- 4.73 kB
- SHA256:
- 8987e1eac62afa4f81246b4666bf143cc7764871167ddfd8cbd9399cafbfc039
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