Sentence Similarity
sentence-transformers
Safetensors
feature-extraction
dense
Generated from Trainer
dataset_size:2979
loss:CosineSimilarityLoss
Instructions to use DChak2000/qwen3-8B-trace-align2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use DChak2000/qwen3-8B-trace-align2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("DChak2000/qwen3-8B-trace-align2") sentences = [ "The earliest predicate succeeded with the same date value in all three positions, yielding the resulting relationship.", "Succeeded: patient_(alice_pays,bob)", "Succeeded: day_to_stamp(\"2004-01-01\",1073001600.0)", "Succeeded: earliest([_20958,_20958,_20958],_20912)" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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