Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
mteb
financial
fiqa
finance
retrieval
rag
esg
fixed-income
equity
Eval Results (legacy)
text-embeddings-inference
Instructions to use mukaj/fin-mpnet-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mukaj/fin-mpnet-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mukaj/fin-mpnet-base") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Inference
- Notebooks
- Google Colab
- Kaggle
Associated model license
2
#3 opened almost 2 years ago
by
Jonas-ML
About input tokens
#2 opened almost 2 years ago
by
JayasriDh
Request for Insights on Fine-Tuning Methods
1
#1 opened almost 2 years ago
by
steven3abc