Image-Text-to-Text
PEFT
Safetensors
English
lora
qwen3.5
vision-language
document-understanding
document-parsing
structured-extraction
json
insurance
legal-documents
ms-swift
vllm
Instructions to use Ashish-Ranjan/Qwen3.5-9B-Policy-Structure-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Ashish-Ranjan/Qwen3.5-9B-Policy-Structure-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-9B") model = PeftModel.from_pretrained(base_model, "Ashish-Ranjan/Qwen3.5-9B-Policy-Structure-LoRA") - Notebooks
- Google Colab
- Kaggle
File size: 3,259 Bytes
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<text x="24" y="34" font-size="18" font-weight="600" fill="#1f1f1f">Held-out policies: original vs fine-tuned</text>
<text x="24" y="56" font-size="13" fill="#6b6b6b">GEICO auto (16 pages) + Encompass home (18 pages), mean of the two; never seen in training</text>
<rect x="190" y="66" width="12" height="12" rx="2" fill="#898781"/><text x="208" y="76" font-size="12" fill="#1f1f1f">Original Qwen3.5-9B (best setting)</text>
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<text x="315.0" y="352" font-size="11" fill="#6b6b6b" text-anchor="middle">25%</text>
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<text x="440.0" y="352" font-size="11" fill="#6b6b6b" text-anchor="middle">50%</text>
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<text x="565.0" y="352" font-size="11" fill="#6b6b6b" text-anchor="middle">75%</text>
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<text x="690.0" y="352" font-size="11" fill="#6b6b6b" text-anchor="middle">100%</text>
<text x="178" y="116" font-size="13" fill="#1f1f1f" text-anchor="end">Node F1</text>
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<text x="374.0" y="109" font-size="12" fill="#1f1f1f" font-weight="400">36%</text>
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<text x="643.2" y="129" font-size="12" fill="#1f1f1f" font-weight="600">89%</text>
<text x="178" y="178" font-size="13" fill="#1f1f1f" text-anchor="end">Right parent (relaxed)</text>
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<text x="488.8" y="171" font-size="12" fill="#1f1f1f" font-weight="400">59%</text>
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<text x="630.8" y="191" font-size="12" fill="#1f1f1f" font-weight="600">87%</text>
<text x="178" y="240" font-size="13" fill="#1f1f1f" text-anchor="end">Node type accuracy</text>
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<text x="460.8" y="233" font-size="12" fill="#1f1f1f" font-weight="400">53%</text>
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<text x="672.0" y="253" font-size="12" fill="#1f1f1f" font-weight="600">95%</text>
<text x="178" y="302" font-size="13" fill="#1f1f1f" text-anchor="end">Text similarity</text>
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<text x="588.0" y="295" font-size="12" fill="#1f1f1f" font-weight="400">78.4%</text>
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<text x="695.2" y="315" font-size="12" fill="#1f1f1f" font-weight="600">99.8%</text>
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