Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
Portuguese
bert
feature-extraction
Eval Results (legacy)
text-embeddings-inference
Instructions to use rufimelo/Legal-BERTimbau-sts-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rufimelo/Legal-BERTimbau-sts-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rufimelo/Legal-BERTimbau-sts-large") sentences = [ "O advogado apresentou as provas ao juíz.", "O juíz leu as provas.", "O juíz leu o recurso.", "O juíz atirou uma pedra." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use rufimelo/Legal-BERTimbau-sts-large with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("rufimelo/Legal-BERTimbau-sts-large") model = AutoModel.from_pretrained("rufimelo/Legal-BERTimbau-sts-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download sentence_bert_config.json from rufimelo/Legal-BERTimbau-sts-large: direct link, hf CLI and curl.
- Browser
- Download file 52 Bytes
-
https://huggingface.co/rufimelo/Legal-BERTimbau-sts-large/resolve/main/sentence_bert_config.json
- Command line
-
hf download hf://rufimelo/Legal-BERTimbau-sts-large/sentence_bert_config.json
-
curl -L -o sentence_bert_config.json https://huggingface.co/rufimelo/Legal-BERTimbau-sts-large/resolve/main/sentence_bert_config.json
52 Bytes
| { | |
| "max_seq_length": 75, | |
| "do_lower_case": false | |
| } |