Sentence Similarity
sentence-transformers
Safetensors
English
mpnet
bert
political-nlp
domain-adaptation
political-debates
text-embeddings-inference
Instructions to use ddore14/Sentence-RooseBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ddore14/Sentence-RooseBERT with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ddore14/Sentence-RooseBERT") 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] - Notebooks
- Google Colab
- Kaggle
File size: 364 Bytes
6113166 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"backend": "tokenizers",
"bos_token": "<s>",
"cls_token": "<s>",
"do_lower_case": true,
"eos_token": "</s>",
"is_local": true,
"mask_token": "<mask>",
"model_max_length": 512,
"pad_token": "<pad>",
"sep_token": "</s>",
"strip_accents": null,
"tokenize_chinese_chars": true,
"tokenizer_class": "MPNetTokenizer",
"unk_token": "[UNK]"
}
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