Instructions to use OpenMatch/Web-Graph-Embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMatch/Web-Graph-Embedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="OpenMatch/Web-Graph-Embedding")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("OpenMatch/Web-Graph-Embedding") model = AutoModel.from_pretrained("OpenMatch/Web-Graph-Embedding") - Notebooks
- Google Colab
- Kaggle
File size: 189 Bytes
18caedc | 1 2 3 4 5 6 7 8 9 10 | {
"tied": true,
"plm_backbone": {
"type": "T5Model",
"feature": "last_hidden_state"
},
"pooling": "first",
"linear_head": false,
"normalize": false
} |