Feature Extraction
sentence-transformers
Safetensors
English
xlm-roberta
retrieval
nuclear-physics
NSR
EXFOR
bge-m3
dense-retrieval
NSR-CPT
text-embeddings-inference
Instructions to use NYSgpt/nsr-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use NYSgpt/nsr-encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NYSgpt/nsr-encoder") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
| [{"idx": 0, "name": "0", "path": "", "type": "sentence_transformers.models.Transformer"}, {"idx": 1, "name": "1", "path": "1_Pooling", "type": "sentence_transformers.models.Pooling"}] |