Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use thtang/ALL_954668 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use thtang/ALL_954668 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("thtang/ALL_954668") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use thtang/ALL_954668 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("thtang/ALL_954668") model = AutoModel.from_pretrained("thtang/ALL_954668") - Notebooks
- Google Colab
- Kaggle
test
Browse files- tokenizer_config.json +22 -0
tokenizer_config.json
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{
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"bos_token": "<s>",
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"clean_up_tokenization_spaces": true,
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"cls_token": "<s>",
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"do_lower_case": true,
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"eos_token": "</s>",
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"mask_token": {
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"__type": "AddedToken",
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"content": "<mask>",
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"lstrip": true,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"model_max_length": 512,
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "<unk>"
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}
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