Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
Generated from Trainer
dataset_size:2036
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use trbeers/distilroberta-base-nli-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use trbeers/distilroberta-base-nli-v0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("trbeers/distilroberta-base-nli-v0") sentences = [ "Proven ability to establish and lead complex projects and programs within a multilayered, hierarchical organization.", "Managed multiple concurrent projects in a large healthcare organization", "Assisted in project documentation without direct management responsibilities", "Skilled in creating presentations using Microsoft PowerPoint" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!