Sentence Similarity
sentence-transformers
Safetensors
English
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:80
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use haf1g/result_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use haf1g/result_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("haf1g/result_model") sentences = [ "A man, woman, and child enjoying themselves on a beach.", "A family of three is at the beach.", "There are two woman in this picture.", "There are children present" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 42fcbf510f2ebefb824ef1dbf89f34dfa0b14e5e1fb78b61d7ede453147a2237
- Size of remote file:
- 5.56 kB
- SHA256:
- f62ce5700621ab6603ba7b587aaba16be007c84e27ad35f2bf6e32cfcc0d92b0
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