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
- Xet hash:
- 12bf04ca7b9a4b4de32e4ef29356ceca46456f295cba9ad7c711075c79c0747d
- Size of remote file:
- 993 MB
- SHA256:
- c391e67d7b2898935d4da9ff71473af38c189e3a78554f9e795f52039899e13b
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