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: 421 Bytes
18caedc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"bos_token": "<s>",
"cls_token": "<s>",
"eos_token": "</s>",
"lower": true,
"n_sentinel_tokens": 512,
"name_or_path": "/data/user_data/peixuanh/ckpts/Web_Graph/web_graph_with_url",
"pad_token": "<pad>",
"sep_token": "</s>",
"special_tokens_map_file": "/data/user_data/peixuanh/models/web_continuous_t5_ckpt/special_tokens_map.json",
"tokenizer_class": "FairseqT5Tokenizer",
"unk_token": "<unk>"
}
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