Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
Generated from Trainer
dataset_size:100029
loss:TripletLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use harcor/all-MiniLM-L6-v2-electrical with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use harcor/all-MiniLM-L6-v2-electrical with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("harcor/all-MiniLM-L6-v2-electrical") sentences = [ "Can I.Q. be improved?", "Can I.Q. be enhanced?", "Q?", "What are the career opportunities after finishing chemical engineering?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!