Sentence Similarity
sentence-transformers
Safetensors
Uzbek
English
bert
feature-extraction
embeddings
uzbek
retrieval
e5
Eval Results (legacy)
text-embeddings-inference
Instructions to use sukhrobnurali/uzbek-e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sukhrobnurali/uzbek-e5-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sukhrobnurali/uzbek-e5-small") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Document sentence-transformers>=5.5.1 requirement
Browse files
README.md
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@@ -106,6 +106,9 @@ scores = q_emb @ p_emb.T
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print(scores) # highest score on the Tashkent passage
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```
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## Evaluation
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The same protocol is applied to the base and fine-tuned models so the delta is a fair
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print(scores) # highest score on the Tashkent passage
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```
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> Requires `sentence-transformers>=5.5.1` — the version the model was saved with.
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> Older versions cannot load it (`ModuleNotFoundError: No module named 'sentence_transformers.base'`).
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## Evaluation
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The same protocol is applied to the base and fine-tuned models so the delta is a fair
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