Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
text-embeddings-inference
Instructions to use TechWolf/ConTeXT-Skill-Extraction-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use TechWolf/ConTeXT-Skill-Extraction-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("TechWolf/ConTeXT-Skill-Extraction-base") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Inference
- Notebooks
- Google Colab
- Kaggle
Update model card: add paper link, license, and update metadata
#2
by nielsr HF Staff - opened
This PR improves the model card for ConTeXT-Skill-Extraction-base by:
- Linking the model to the paper: WorkRB: A Community-Driven Evaluation Framework for AI in the Work Domain.
- Updating the
pipeline_tagtotext-retrievalto better reflect its function in the WorkRB benchmark. - Adding the
apache-2.0license. - Adding a link to the official WorkRB GitHub repository.
- Providing more domain-relevant sample sentences in the usage snippet.