Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
Generated from Trainer
dataset_size:4893
loss:TripletLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use greatakela/gennlp_hw1_encoder2025 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use greatakela/gennlp_hw1_encoder2025 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("greatakela/gennlp_hw1_encoder2025") sentences = [ "I almost envy you your assignment. I see in your mind that you are tempted to take my place. Not correct, Doctor, although I am aware of your mind attempting to contact mine. Were you born a telepath? Yes. That is why I had to study on Vulcan. I understand. May I show you to your quarters?[SEP]I think I'll stay here a bit. Ambassador Kollos often finds the process of transport somewhat unsettling.", " I don't see anything, do you?", "I understand. Our ship's surgeon often makes the same complaint. Do call when you are ready.", "Irrelevant, since we are here." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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