Instructions to use Labib11/pmc-uae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Labib11/pmc-uae with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Labib11/pmc-uae")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Labib11/pmc-uae") model = AutoModel.from_pretrained("Labib11/pmc-uae") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- caadb894164af9ade31b72239b35f36c4e87a1bad90ddd0b6b28e12193601eb0
- Size of remote file:
- 1.34 GB
- SHA256:
- 794e71e443ed1a70ab6da59b293e245eb20928bdcfe1f8f263cc3328b39af3c5
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