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
File size: 205 Bytes
fa28930 | 1 2 3 4 5 6 7 8 9 10 | {
"__version__": {
"sentence_transformers": "3.4.1",
"transformers": "4.48.3",
"pytorch": "2.2.0+cu121"
},
"prompts": {},
"default_prompt_name": null,
"similarity_fn_name": "cosine"
} |