Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:12623
loss:ContrastiveLoss
text-embeddings-inference
Instructions to use sch-allie/bert_persona with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sch-allie/bert_persona with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sch-allie/bert_persona") sentences = [ "I like to read, My favorite color is blue, I have brown hair, I work at a grocery store, I like cupcakes, Marduk is my favorite band, Lutefisk is the best dish in the whole world, I recently moved to sweden, I always seem to be losing things , most recently , my mind, I enjoy hiking on glaciers", "I am a writer, I enjoy going to museums, I have ten nieces and nephews, I am married, I enjoy my job , as a teacher, I enjoy video games, I enjoy singing, Magic mike is my favorite movie, I live in a big city", "I am east asian, Pizza is my favorite, I try to watch what i eat, I enjoy eating italian food, I enjoy visiting museums, We have two sons, I like to paint, I like to attend wine tours, My husband is 20 years older than me", "I like cupcakes, I like to read, I work at a grocery store, My favorite color is blue, I currently suffer from social anxiety, I am a geology major at alabama university, I never have had alcohol in my life, I have a girlfriend of 7 years" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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