Text Classification
Transformers
Safetensors
PEFT
English
retrievalrouter
feature-extraction
retrieval
document-retrieval
information-retrieval
routing
RAG
query-routing
late-interaction
lora
custom_code
Instructions to use emrekuruu/RetrievalRouter-lambda-l30 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emrekuruu/RetrievalRouter-lambda-l30 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="emrekuruu/RetrievalRouter-lambda-l30", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("emrekuruu/RetrievalRouter-lambda-l30", trust_remote_code=True, device_map="auto") - PEFT
How to use emrekuruu/RetrievalRouter-lambda-l30 with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
ba31fb4 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:f11f4a9f699915110fad6a0e488ec310f7bffbf07acd90ffea1344de0805d708
size 2384257484
|