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-450 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-450 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sobamchan/roberta-base-mean-softmax-450") 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
- Xet hash:
- fa4fa6220162d10f8a882804e3fd68833399bc71fbb89fb20df033b306076d2f
- Size of remote file:
- 993 MB
- SHA256:
- cc9d3590215c1a9184b7f6ba3b79c942d4ec6c3e311a7707f88e320f3761419a
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