Sentence Similarity
sentence-transformers
Safetensors
English
roberta
feature-extraction
Generated from Trainer
dataset_size:942069
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use sobamchan/roberta-base-mean-softmax-250 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sobamchan/roberta-base-mean-softmax-250 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sobamchan/roberta-base-mean-softmax-250") sentences = [ "Two women having drinks and smoking cigarettes at the bar.", "Women are celebrating at a bar.", "Two kids are outdoors.", "The four girls are attending the street festival." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "__version__": { | |
| "sentence_transformers": "3.4.1", | |
| "transformers": "4.48.3", | |
| "pytorch": "2.2.0+cu121" | |
| }, | |
| "prompts": {}, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |