Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
text-embeddings-inference
Instructions to use mpalinski/ConTeXT-ESCO-Matcher with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mpalinski/ConTeXT-ESCO-Matcher with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mpalinski/ConTeXT-ESCO-Matcher") 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] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e2fd06be1215e9ef241e68092ace762cd2768ec03b3e0575991540e8871ea8d
- Size of remote file:
- 23 MB
- SHA256:
- 719a794a56728c628b1e9f4233c2f73b74f9b3feca43f19f97a2c4246ae03a62
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