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
Commit ·
9d195f1
1
Parent(s): 7afdbde
Pushing trained model
Browse files- tokenizer.json +0 -0
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|