Sentence Similarity
sentence-transformers
Safetensors
phi3
feature-extraction
dense
Generated from Trainer
dataset_size:5749
loss:CosineSimilarityLoss
custom_code
Eval Results (legacy)
Instructions to use AntoineGourru/FT_phi_cos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AntoineGourru/FT_phi_cos with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AntoineGourru/FT_phi_cos", trust_remote_code=True) sentences = [ "A man is playing the guitar.", "A man plays an acoustic guitar.", "Ryanair chief hails report findings", "2 British soldiers killed in Afghan insider attack" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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