Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
dense
Generated from Trainer
dataset_size:404
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use hast2/2026-paraphrase_mpnet_influence_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hast2/2026-paraphrase_mpnet_influence_v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hast2/2026-paraphrase_mpnet_influence_v2") sentences = [ "I am part or particle of God.", "Now let us, as we float along,", "Talk of a divinity in man!", "And pray that never child of song" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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