Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use anatel/bert-augmented-pt-anatel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use anatel/bert-augmented-pt-anatel with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("anatel/bert-augmented-pt-anatel") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use anatel/bert-augmented-pt-anatel with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("anatel/bert-augmented-pt-anatel") model = AutoModel.from_pretrained("anatel/bert-augmented-pt-anatel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3bbecaee1698599902fb5c148ed7cfe643b4d1b35845f6a05b0363f788d7a36b
- Size of remote file:
- 436 MB
- SHA256:
- 61e4a2a752a96637b09e9309b5caa4cc3a6319eb0f8fa8679dce0522ba2a2b98
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