Falcon-H1R-7B UAE Laws LoRA Adapter
A LoRA adapter for tiiuae/Falcon-H1R-7B finetuned on UAE Federal Laws to provide legal analysis in IRAC format.
What is IRAC?
IRAC is a legal analysis framework:
- Issue: Identifies the legal question
- Rule: Cites the relevant law/article
- Application: Explains how the rule applies to the situation
- Conclusion: Provides the final answer
Quick Start Options
| Method | Best For |
|---|---|
| GGUF + Ollama | Local deployment, easy setup |
| Python + LoRA | Custom integration, fine-tuning |
GGUF + Ollama (Recommended)
The easiest way to run this model locally is with Ollama.
1. Install Ollama
curl -fsSL https://ollama.com/install.sh | sh
2. Download the GGUF
# Download from HuggingFace
wget https://huggingface.co/SalahALHaismawi/falcon-h1r-uae-laws/resolve/main/falcon-h1r-uae-laws.gguf
3. Create a Modelfile
Create a file named Modelfile:
FROM ./falcon-h1r-uae-laws.gguf
TEMPLATE """### Instruction:
{{ .Prompt }}
### Response:
"""
PARAMETER stop "### Instruction:"
PARAMETER temperature 0.1
4. Create and Run
# Create the model in Ollama
ollama create falcon-uae-laws -f Modelfile
# Run inference
ollama run falcon-uae-laws "What are the penalties for drunk driving in the UAE?"
Example Ollama Output
Issue: Drunk driving penalties. Rule: Under UAE Federal Decree-Law No. 14 of 2020
(amending the Penal Code) and the Federal Traffic Law, driving under the influence
of alcohol is a criminal offence punishable by imprisonment and or a fine...
Training Dataset
UAE Laws Q&A Dataset (IRAC Format)
- 9,477 samples of UAE legal Q&A pairs
- 100% IRAC format consistency
- 83.8% cite specific article numbers
- Human-written seed data (~1,000 pairs) + synthetic generation with human validation
from datasets import load_dataset
dataset = load_dataset("SalahALHaismawi/uae-laws-irac")
Example Outputs
Example 1: Criminal Law
Question: What are the penalties for drunk driving in the UAE?
Response:
Issue: Drunk driving penalties. Rule: Under UAE Federal Decree-Law No. 14 of 2020 (amending the Penal Code) and the Federal Traffic Law, driving under the influence of alcohol is a criminal offence punishable by imprisonment and or a fine, with penalties increasing if damage, injury, or death is caused. Application: Anyone who drives a vehicle while intoxicated may be punished by imprisonment and a fine as determined by the court. If the offence results in damage to property, bodily injury, or death, stricter penalties including longer imprisonment and higher fines may be imposed. Conclusion: Drunk driving in the UAE is a serious offence with penalties that escalate depending on the harm caused.
Example 2: Labor Law
Question: What happens if an employer terminates an employee without notice in the UAE?
Response:
Issue: Employer terminates without notice. Rule: Article 44 of Federal Decree-Law No. 33 of 2021 permits termination without notice only in specific circumstances. Article 47 provides compensation where termination is unlawful. Application: If an employer terminates an employee without notice and without a valid legal reason, the employee is entitled to compensation of up to three months' salary, in addition to notice pay and other contractual entitlements. Conclusion: An employer who unlawfully terminates an employee without notice must compensate the employee in accordance with UAE Labour Law.
Example 3: Property Law
Question: What are the rules regarding property ownership for foreigners in the UAE?
Response:
Issue: Can foreigners own property in the UAE? Rule: Foreigners may own property only in areas designated by the relevant Emirate, subject to applicable laws and regulations. Application: Emirate-level legislation determines the specific freehold or usufruct areas where foreign ownership is permitted. Conclusion: Foreigners may own property in the UAE only in designated areas and in accordance with Emirate-specific regulations.
Python Usage
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
from peft import PeftModel
import torch
# Load with 8-bit quantization (required)
tokenizer = AutoTokenizer.from_pretrained("tiiuae/Falcon-H1R-7B", trust_remote_code=True)
bnb_config = BitsAndBytesConfig(load_in_8bit=True)
base_model = AutoModelForCausalLM.from_pretrained(
"tiiuae/Falcon-H1R-7B",
quantization_config=bnb_config,
device_map="auto",
max_memory={0: "15GiB"}, # Prevents CPU offloading issues
trust_remote_code=True
)
# Load the LoRA adapter
model = PeftModel.from_pretrained(base_model, "SalahALHaismawi/falcon-h1r-uae-laws-lora")
model.eval()
# Generate response
question = "What are the penalties for drunk driving in the UAE?"
prompt = f"### Instruction:\n{question}\n\n### Response:\n"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
with torch.no_grad():
output = model.generate(
**inputs,
max_new_tokens=400,
do_sample=False,
pad_token_id=tokenizer.eos_token_id
)
response = tokenizer.decode(output[0], skip_special_tokens=True)
print(response.split("### Response:")[-1].strip())
Training Details
| Parameter | Value |
|---|---|
| Base Model | tiiuae/Falcon-H1R-7B |
| Method | LoRA (Low-Rank Adaptation) |
| Rank (r) | 32 |
| Alpha | 64 |
| Dropout | 0.05 |
| Target Modules | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj |
| Training Data | UAE Federal Laws |
Available Files
| File | Size | Description |
|---|---|---|
falcon-h1r-uae-laws.gguf |
~15GB | Quantized model for Ollama/llama.cpp |
adapter_model.safetensors |
~134MB | LoRA adapter weights |
adapter_config.json |
- | LoRA configuration |
Important Notes
8-bit quantization is required for Python usage - The model produces incorrect outputs without it
GGUF works out of the box - No quantization setup needed when using Ollama
RAG Implementation is recommended: This fine-tune teaches the model IRAC format aligned with UAE legal text. For the most accurate legal output, implement a document retriever or web-crawler to reduce hallucinations and ground the truth.
Use the exact prompt format shown above for best results
Legal Disclaimer: This model is for educational purposes only. Always consult a qualified legal professional for actual legal advice.
Model Architecture
Falcon-H1R-7B is a hybrid architecture combining:
- Mamba (State Space Model) layers for efficient sequence processing
- Attention layers for complex reasoning
This makes it particularly efficient for long legal documents.
License
Apache 2.0 (following the base model license)
Author
Salah AlHaismawi
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