Instructions to use yash-412/trained_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yash-412/trained_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="yash-412/trained_model")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("yash-412/trained_model") model = AutoModelForSpeechSeq2Seq.from_pretrained("yash-412/trained_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa1a68a7181d0d0c7b94f7e582a35f3dbe36e739e4103b466ca1ae2901dd1caf
- Size of remote file:
- 4.86 kB
- SHA256:
- b78c54d085972a68d155e6d126ecbe17a45622f06fbfd3137d4ac81f2637e4cf
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