Sentence Similarity
sentence-transformers
PyTorch
Safetensors
English
mpnet
feature-extraction
medical
biology
text-embeddings-inference
Instructions to use SlimTse/BioLORD-2023 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use SlimTse/BioLORD-2023 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SlimTse/BioLORD-2023") sentences = [ "bartonellosis", "cat scratch disease", "cat scratch wound", "tick-borne orbivirus fever", "cat fur" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [5, 5] - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "mask_token": { | |
| "content": "<mask>", | |
| "lstrip": true, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "unk_token": "[UNK]" | |
| } | |