Gemma 4 E4B — Document Classifier (LoRA)
LoRA adapter finetuned from google/gemma-4-E4B-it for single-page document
classification and identity-field extraction from scanned/faxed financial documents.
Classes
bank_statement, drivers_license, monthly_bill, paystub, state_id, unknown
Output format
{"schema_object_wrapper": [{"cls": "", "confidence": 0.0, "issuer": "", "holder": "", "page_marker": ""}]}
Usage
from unsloth import FastVisionModel
model, processor = FastVisionModel.from_pretrained("asim-salim/gemma-4-e4b-doc-classifier-lora")
FastVisionModel.for_inference(model)
Adapter: 147 MB LoRA over google/gemma-4-E4B-it. Trained with unsloth + TRL (PEFT 0.19.1).
License
Governed by the Gemma Terms of Use and the Gemma Prohibited Use Policy.
Limitations
Trained on a specific document corpus; not evaluated for general-purpose document understanding. Outputs must not be treated as authoritative for financial decisions.
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