Sentence Similarity
sentence-transformers
Safetensors
German
bert
linktransformer
tabular-classification
text-embeddings-inference
Instructions to use dell-research-harvard/lt-wikidata-comp-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dell-research-harvard/lt-wikidata-comp-de with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dell-research-harvard/lt-wikidata-comp-de") sentences = [ "Das ist eine glückliche Person", "Das ist ein glücklicher Hund", "Das ist eine sehr glückliche Person", "Heute ist ein sonniger Tag" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Updated model with better training and evaluation. Test and val data included as pickle files. Older Legacy files were removed to avoid confusion.
1668b31 | epoch,steps,cos_sim-Accuracy@1,cos_sim-Accuracy@3,cos_sim-Accuracy@5,cos_sim-Accuracy@10,cos_sim-Precision@1,cos_sim-Recall@1,cos_sim-Precision@3,cos_sim-Recall@3,cos_sim-Precision@5,cos_sim-Recall@5,cos_sim-Precision@10,cos_sim-Recall@10,cos_sim-MRR@10,cos_sim-NDCG@10,cos_sim-MAP@100 | |
| 0,0,0.5484683172471674,0.6160302140159463,0.6416281997482165,0.6689047419219472,0.5484683172471674,0.38222128969086583,0.27262554203385087,0.5130158064064904,0.17792698279479646,0.5476220450412644,0.0946705832983634,0.5788396978598406,0.5883317014034596,0.541931341424033,0.507100878614985 | |