Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:200
loss:CoSENTLoss
text-embeddings-inference
Instructions to use moshew/gist_small_ft_gooaq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use moshew/gist_small_ft_gooaq with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("moshew/gist_small_ft_gooaq") sentences = [ "who is imf chief economist?", "Metoprolol succinate is also known by the brand name Toprol XL. It is the extended-release form of metoprolol. Metoprolol succinate is approved to treat high blood pressure, chronic chest pain, and congestive heart failure.", "He wants to confirm if he is talking to Priya or Angel Priya (I.e., if he is really talking to a girl or just a guy with fake profile) They are talking to you and want to see how you look. I found it normal but would say, be careful about whom do you share your picture with as they might misuse it. I hate this one.", "A Dependent Care Flexible Spending Account, or “FSA,” is a pre-tax benefit account used to pay for dependent care services while you are at work. The money you contribute to a Dependent Care FSA is not subject to payroll taxes, so you end up paying less in taxes and taking home more of your paycheck." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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