Sentence Similarity
sentence-transformers
PyTorch
Transformers
Portuguese
bert
feature-extraction
text-embeddings-inference
Instructions to use melll-uff/pt-br_simcse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use melll-uff/pt-br_simcse with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("melll-uff/pt-br_simcse") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use melll-uff/pt-br_simcse with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("melll-uff/pt-br_simcse") model = AutoModel.from_pretrained("melll-uff/pt-br_simcse", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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