How to use rufimelo/Legal-BERTimbau-sts-base-ma with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rufimelo/Legal-BERTimbau-sts-base-ma") 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]
How to use rufimelo/Legal-BERTimbau-sts-base-ma with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("rufimelo/Legal-BERTimbau-sts-base-ma") model = AutoModel.from_pretrained("rufimelo/Legal-BERTimbau-sts-base-ma", device_map="auto")
https://huggingface.co/rufimelo/Legal-BERTimbau-sts-base-ma/resolve/main/tokenizer.json
hf download hf://rufimelo/Legal-BERTimbau-sts-base-ma/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/rufimelo/Legal-BERTimbau-sts-base-ma/resolve/main/tokenizer.json
