Instructions to use HakHan/Web-Graph-Embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HakHan/Web-Graph-Embedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="HakHan/Web-Graph-Embedding")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("HakHan/Web-Graph-Embedding") model = AutoModel.from_pretrained("HakHan/Web-Graph-Embedding") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d54a12de08a8850a557497ea516dd124862768b1d9e4ccc7c18f59664c1da9a
- Size of remote file:
- 903 MB
- SHA256:
- c5a3389af594da7419195fc12cad061c544f5f3e332398ffc4fc0b044c2963d0
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