Text Classification
Transformers
Safetensors
PEFT
English
retrievalrouter
feature-extraction
retrieval
document-retrieval
information-retrieval
routing
RAG
query-routing
late-interaction
lora
baseline
custom_code
Instructions to use emrekuruu/RetrievalRouter_Baseline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emrekuruu/RetrievalRouter_Baseline with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="emrekuruu/RetrievalRouter_Baseline", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("emrekuruu/RetrievalRouter_Baseline", trust_remote_code=True, device_map="auto") - PEFT
How to use emrekuruu/RetrievalRouter_Baseline with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Commit History
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Use arXiv citation
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Update paper link to real arXiv (2608.25625)
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Fix baseline citation (Arabzadeh et al., CIKM 2021)
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Delete files configuration_irouterlm.py modeling_irouterlm.py with huggingface_hub
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Set model_type=retrievalrouter
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Rename custom code to RetrievalRouter
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Rename custom code to RetrievalRouter
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Add baseline model card
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Upload tokenizer
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Upload model
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initial commit
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