Sentence Similarity
sentence-transformers
Safetensors
qwen2
feature-extraction
Generated from Trainer
dataset_size:2859594
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use AlexWortega/qwen1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AlexWortega/qwen1k with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AlexWortega/qwen1k") sentences = [ "How old is Garry Marshall?", "Garry Marshall\nOn the morning of July 19, 2016, Marshall died at a hospital in Burbank, California at the age of 81 due to complications of pneumonia after suffering a stroke.[20][21]", "Gregg Marshall\nMichael Gregg Marshall (born February 27, 1963) is an American college basketball coach who currently leads the Shockers team at Wichita State University. Marshall has coached his teams to appearances in the NCAA Men's Division I Basketball Tournament in twelve of his eighteen years as a head coach. He is the most successful head coach in Wichita State University history (261 wins), and is also the most successful head coach in Winthrop University history (194 wins).", "Guillotine\nFor a period of time after its invention, the guillotine was called a louisette. However, it was later named after Guillotin who had proposed that a less painful method of execution should be found in place of the breaking wheel, though he opposed the death penalty and bemoaned the association of the guillotine with his name." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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