Instructions to use Isma/test_7000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isma/test_7000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Isma/test_7000")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Isma/test_7000") model = AutoModel.from_pretrained("Isma/test_7000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47d341b7ea0b797a946bf0f90a2b60fb2714daf9d7972fb0dfa968d6f808bb8b
- Size of remote file:
- 378 MB
- SHA256:
- edd605966c20724ff6b0d15fdddab84851aa9376998a783448d977ace9d67475
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