Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
Generated from Trainer
dataset_size:84915
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use scroobiustrip/mpnet-direction-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use scroobiustrip/mpnet-direction-finetuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("scroobiustrip/mpnet-direction-finetuned") sentences = [ "send money from south africa to belgium", "money transfer to estonia from slovenia", "transfer money online from belgium to south africa", "send money abroad to belgium from south africa" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from scroobiustrip/mpnet-direction-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/scroobiustrip/mpnet-direction-finetuned/resolve/main/tokenizer.json
- Command line
-
hf download hf://scroobiustrip/mpnet-direction-finetuned/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/scroobiustrip/mpnet-direction-finetuned/resolve/main/tokenizer.json
711 kB
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