Sentence Similarity
sentence-transformers
Safetensors
English
feature-extraction
Generated from Trainer
dataset_size:80448369
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
Instructions to use AdamLucek/static-retrieval-mrl-MBERT-base-en-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AdamLucek/static-retrieval-mrl-MBERT-base-en-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AdamLucek/static-retrieval-mrl-MBERT-base-en-v1") sentences = [ "how to sign legal documents as power of attorney?", "After the principal's name, write “by” and then sign your own name. Under or after the signature line, indicate your status as POA by including any of the following identifiers: as POA, as Agent, as Attorney in Fact or as Power of Attorney.", "Most earthquakes occur along the edge of the oceanic and continental plates. The earth's crust (the outer layer of the planet) is made up of several pieces, called plates. The plates under the oceans are called oceanic plates and the rest are continental plates.", "Go to System -> VDOM -> VDOM2 and select 'Delete'. This VDOM is now successfully removed from the configuration." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a55415781b561b9eeb476eaab60a8dbd91fd42b2ce0e951486521cebcaafa74b
- Size of remote file:
- 206 MB
- SHA256:
- 0862cf98ed3d736505729510296096558f8b64bc578b035d603b81d62be3b588
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