Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dataset_size:10K<n<100K
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use Hgkang00/FT-label-consent-20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Hgkang00/FT-label-consent-20 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Hgkang00/FT-label-consent-20") sentences = [ "Driving or commuting to work feels draining, even if it's a short distance.", "Symptoms during a manic episode include decreased need for sleep, more talkative than usual, flight of ideas, distractibility", "I feel like I have lost a part of myself since the traumatic event, and I struggle to connect with others on a deeper level.", "Diagnosis requires at least one hypomanic episode and one major depressive episode." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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