Instructions to use enrybds/firstmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use enrybds/firstmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="enrybds/firstmodel")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("enrybds/firstmodel") model = AutoModelForCTC.from_pretrained("enrybds/firstmodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22fb77871f225bc9bf84c13bb337be59300a81ceaeec4cd23e1cdcecf090adbd
- Size of remote file:
- 3.31 kB
- SHA256:
- 03e2f13ed0e40457d37328f5b3caaf08767d8b4de1b2a4f0058d61609e5c5c65
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