Sentence Similarity
sentence-transformers
TensorBoard
Safetensors
Portuguese
bert
feature-extraction
Trained with AutoTrain
text-embeddings-inference
Instructions to use cnmoro/micro-bertim-embeddings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use cnmoro/micro-bertim-embeddings with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cnmoro/micro-bertim-embeddings") sentences = [ "search_query: i love autotrain", "O pôr do sol pinta o céu com tons de laranja e vermelho", "Joana adora estudar matemática nas tardes de sábado", "Os pássaros voam em formação, criando um espetáculo no horizonte" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 526a4b2d5df284251b3b01da02ce1d78e33a2e9f9c46293d49d3ae182b76897d
- Size of remote file:
- 5.56 kB
- SHA256:
- 34bd507f1ad42d95cd5e96796ed80be352f247c8f189253bf9101d58b1e07749
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