sentence-transformers
Safetensors
Turkish
turkish
legal
rag
retrieval-augmented-generation
mevzuat
lora
cross-encoder
Instructions to use 0xBatuhan4/ceng493-rag-bundle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use 0xBatuhan4/ceng493-rag-bundle with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("0xBatuhan4/ceng493-rag-bundle") query = "Which planet is known as the Red Planet?" passages = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." ] scores = model.predict([(query, passage) for passage in passages]) print(scores) - Notebooks
- Google Colab
- Kaggle
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