Sentence Similarity
sentence-transformers
Safetensors
English
roberta
feature-extraction
dataset_size:100K<n<1M
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use mrm8488/distilroberta-base-ft-allnli-matryoshka-768-16-1e-128bs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mrm8488/distilroberta-base-ft-allnli-matryoshka-768-16-1e-128bs with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mrm8488/distilroberta-base-ft-allnli-matryoshka-768-16-1e-128bs") sentences = [ "Test Rocks", "Number of testimonies", "People are at a pool.", "I've never been to Asia" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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