Sentence Similarity
sentence-transformers
Safetensors
Japanese
luke
linktransformer
tabular-classification
Instructions to use dell-research-harvard/lt-wikidata-comp-ja with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dell-research-harvard/lt-wikidata-comp-ja with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dell-research-harvard/lt-wikidata-comp-ja") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
File size: 2,237 Bytes
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"added_tokens_decoder": {
"0": {
"content": "<s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"1": {
"content": "<pad>",
"lstrip": false,
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"special": true
},
"2": {
"content": "</s>",
"lstrip": false,
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"single_word": false,
"special": true
},
"3": {
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},
"32769": {
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"32770": {
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},
"32771": {
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"special": true
}
},
"additional_special_tokens": [
"<ent>",
"<ent2>",
"<ent>",
"<ent2>",
"<ent>",
"<ent2>",
"<ent>",
"<ent2>"
],
"bos_token": "<s>",
"clean_up_tokenization_spaces": true,
"cls_token": "<s>",
"entity_mask2_token": "[MASK2]",
"entity_mask_token": "[MASK]",
"entity_pad_token": "[PAD]",
"entity_token_1": {
"__type": "AddedToken",
"content": "<ent>",
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},
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},
"entity_unk_token": "[UNK]",
"eos_token": "</s>",
"mask_token": "<mask>",
"max_entity_length": 32,
"max_mention_length": 30,
"model_max_length": 512,
"pad_token": "<pad>",
"sep_token": "</s>",
"sp_model_kwargs": {},
"task": null,
"tokenizer_class": "MLukeTokenizer",
"unk_token": "<unk>"
}
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