Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use Akshayextreme/SemEval_2015_PIT_biencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Akshayextreme/SemEval_2015_PIT_biencoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Akshayextreme/SemEval_2015_PIT_biencoder") 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 Akshayextreme/SemEval_2015_PIT_biencoder with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Akshayextreme/SemEval_2015_PIT_biencoder") model = AutoModel.from_pretrained("Akshayextreme/SemEval_2015_PIT_biencoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8395d32f986affd4599ea1098280aa44d3ccc08ce93578bf2e8d66932d0d2374
- Size of remote file:
- 90.9 MB
- SHA256:
- d9eba7d5487c971ee6690e108c9262a3d5cdb0f1327962416d32ca595922a138
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