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vivekvar/qwen3-14b-pocso-legal-assistant

sourceHugging Faceapache-2.0updated 8mo agoView on Hugging Face
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Qwen3-14B Fine-tuned for Indian Legal Domain (POCSO Investigation Assistant)

Model Description

This is a LoRA fine-tuned version of Qwen/Qwen3-14B specifically trained for Indian legal domain tasks, with a focus on POCSO (Protection of Children from Sexual Offences) Act cases.

Model Details

PropertyValue
Base ModelQwen/Qwen3-14B
Fine-tuning MethodLoRA (Low-Rank Adaptation)
LoRA Rank (r)64
LoRA Alpha128
Dropout0.05
Target Modulesqproj, kproj, vproj, oproj, gateproj, upproj, down_proj
Training Examples8,954
Validation Examples1,054
Epochs3
Learning Rate2e-5

Training Data

The model was fine-tuned on Indian legal case examples including:

  • —POCSO Act cases and sections
  • —IPC (Indian Penal Code) provisions
  • —BNS (Bharatiya Nyaya Sanhita) 2023 sections
  • —CrPC/BNSS procedural guidelines
  • —Real anonymized complaint documents in English and Telugu

Capabilities

1. SUGGEST_SECTIONS

Suggests applicable legal sections based on complaint text.

2. GENERATE_SUMMARY

Extracts key details (victim, accused, incident) from complaints.

3. IDENTIFY_EVIDENCE

Recommends evidence collection priorities.

Usage

python
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

# Load base model
base_model = AutoModelForCausalLM.from_pretrained(
    "Qwen/Qwen3-14B",
    torch_dtype="auto",
    device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-14B")

# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "vivekvar/qwen3-14b-pocso-legal-assistant")

# Generate
prompt = """Task: Suggest legal sections for this complaint.

Complaint: A 15-year-old girl was harassed by her neighbor.

Output JSON:"""

inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.1)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Evaluation Results

MetricScore
Semantic Similarity77.8%
JSON Output Validity100%
Reliability100%
Model GradeEXCELLENT

Comparison with GPT + RAG

TaskQwen3-14B (this)GPT + RAG
SUGGEST_SECTIONS70%0% (refuses)
GENERATE_SUMMARY85%75%
Reliability100%66.7%

Limitations

  1. 1.May apply wrong law (BNS vs IPC) for cases before July 2024
  2. 2.May miss mandatory POCSO sections in edge cases
  3. 3.Evidence recommendations less detailed than RAG systems
  4. 4.Optimized for English and Telugu

Disclaimer

⚠️ This model is an AI assistant and should NOT replace professional legal advice.

All suggestions must be verified by qualified legal professionals.

License

Apache 2.0

Citation

bibtex
@misc{qwen3-14b-pocso-legal,
  title={Qwen3-14B Fine-tuned for Indian Legal Domain},
  author={AI4AP Team},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/vivekvar/qwen3-14b-pocso-legal-assistant}
}