Instructions to use on1onmangoes/HF_Example with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use on1onmangoes/HF_Example with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="on1onmangoes/HF_Example")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("on1onmangoes/HF_Example") model = AutoModelForSpeechSeq2Seq.from_pretrained("on1onmangoes/HF_Example") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 818fa4b382ef31a40f29f4f787229ea6a8981e1c25cf56f905ebd00ceabd339f
- Size of remote file:
- 6.17 GB
- SHA256:
- 53dc25c0e5988259f54a5ed601f8d5831e310f13414db4d80ac39af6405010b0
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