Feature Extraction
sentence-transformers
Safetensors
mpnet
sentence-similarity
dense
Generated from Trainer
dataset_size:4615
loss:TripletLoss
text-embeddings-inference
Instructions to use FritzStack/mpnet_MH_embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use FritzStack/mpnet_MH_embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("FritzStack/mpnet_MH_embedding") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle