---
language:
- en
license: llama3.2
base_model: meta-llama/Llama-3.2-3B-Instruct
library_name: transformers
tags:
- legal
- immigration
- fine-tuned
- llama
- united-states
- lora
datasets:
- nshportun/usa-immigration-law-qa
pipeline_tag: text-generation
---

# USA Immigration Law --- Llama 3.2 3B Fine-Tuned

> **A 3B fine-tuned model that outperforms the Llama 3 8B zero-shot baseline on U.S. immigration law Q&A
> (+27% mean score, 4x more fully-correct answers).**

Fine-tuned from [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct)
on the [nshportun/usa-immigration-law-qa](https://huggingface.co/datasets/nshportun/usa-immigration-law-qa)
dataset --- **17,058 source-grounded Q&A pairs** covering all major U.S. immigration subdomains.

## Benchmark Results

Evaluated on 101 held-out questions scored 0-3 by Claude Sonnet 4.6 as judge:

| Model | Mean Score (0-3) | % Fully Correct (3) |
|-------|-----------------|---------------------|
| Claude Sonnet 4.6 (zero-shot) | 1.515 | 24.8% |
| **Llama 3.2 3B fine-tuned (this model)** | **1.079** | **16.8%** |
| Llama 3 8B zero-shot | 0.851 | 4.0% |

Domain-specific fine-tuning at 3B scale delivers **+27% higher mean score** and **4x more fully-correct answers**
compared to a larger general-purpose 8B model.

## Training Details

| Setting | Value |
|---------|-------|
| LoRA rank (r) | 32 |
| LoRA alpha | 64 |
| Target modules | q_proj, v_proj, k_proj, o_proj |
| LoRA dropout | 0.05 |
| Epochs | 2 |
| Learning rate | 5e-5 |
| Batch size | 2 |
| Max sequence length | 1024 |
| Training pairs | 16,065 |
| Infrastructure | ml.g5.2xlarge (AWS SageMaker) |

## Usage

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "nshportun/usa-immigration-llama-3.2-3b-v3"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto")

messages = [
    {"role": "system", "content": "You are an expert on U.S. immigration law and policy. Answer accurately based on USCIS, 8 CFR, and BIA sources."},
    {"role": "user", "content": "What is the filing fee for Form I-485?"},
]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
out = model.generate(**inputs, max_new_tokens=300, do_sample=False)
print(tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
```

## Dataset

The model was trained on [nshportun/usa-immigration-law-qa](https://huggingface.co/datasets/nshportun/usa-immigration-law-qa),
a dataset of 17,058 source-grounded Q&A pairs from official U.S. immigration sources (USCIS Policy Manual,
8 CFR/INA, BIA Precedent Decisions, USCIS Forms, DHS/CBP Statistics).

## Disclaimer

For **research and educational purposes only**. Not legal advice.
Always consult a licensed immigration attorney.