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0xBatuhan4
/
ceng493-rag-bundle

sentence-transformers
Safetensors
Turkish
turkish
legal
rag
retrieval-augmented-generation
mevzuat
lora
cross-encoder
Model card Files Files and versions
xet
Community

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
ceng493-rag-bundle
13.7 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 15 commits
0xBatuhan4's picture
0xBatuhan4
Remove duplicate top-level generation_config.json (kept merged/ version)
e96d30a verified about 2 months ago
  • embed-tr-legal-v2
    Phase 13b: upload embed FT v2 (multilingual-e5-base + clean corpus pairs) about 2 months ago
  • llm-vanilla-clean
    Remove duplicate top-level generation_config.json (kept merged/ version) about 2 months ago
  • reranker-tr-legal-v2
    Phase 13b: upload reranker FT v2 (bge-reranker-v2-m3 + clean corpus pairs) about 2 months ago
  • .gitattributes
    1.81 kB
    Add llm-vanilla-clean (Phase 13 LLM LoRA merged (9.6 GB)) about 2 months ago
  • LICENSE
    1.87 kB
    Init: README (model card) + MIT LICENSE about 2 months ago
  • README.md
    5.71 kB
    Add model card about 2 months ago