Text Classification
sentence-transformers
Safetensors
English
intent-classification
clinc150
out-of-scope-detection
contrastive-learning
Instructions to use Amitava25/clinc150-contrastive-mpnet-maxsim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Amitava25/clinc150-contrastive-mpnet-maxsim with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Amitava25/clinc150-contrastive-mpnet-maxsim") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!