Minibase/DeId-Small

   # Clone and build llama.cpp
   git clone https://github.com/ggerganov/llama.cpp
   cd llama.cpp
   make

   # Return to project directory
   cd ../de-id-small

   # Download model files from HuggingFace
   wget https://huggingface.co/Minibase/DeId-Small/resolve/main/model.gguf
   wget https://huggingface.co/Minibase/DeId-Small/resolve/main/deid_inference.py
   wget https://huggingface.co/Minibase/DeId-Small/resolve/main/config.json
   wget https://huggingface.co/Minibase/DeId-Small/resolve/main/tokenizer_config.json
   wget https://huggingface.co/Minibase/DeId-Small/resolve/main/generation_config.json

   # Start llama.cpp server with the GGUF model
   ../llama.cpp/llama-server \
     -m model.gguf \
     --host 127.0.0.1 \
     --port 8000 \
     --ctx-size 2048 \
     --n-gpu-layers 0 \
     --chat-template

   import requests

   # De-identify text via REST API
   response = requests.post("http://127.0.0.1:8000/completion", json={
       "prompt": "Instruction: De-identify this text by replacing all personal information with placeholders.\n\nInput: Patient John Smith, born 1985-03-15, lives at 123 Main St.\n\nResponse: ",
       "max_tokens": 256,
       "temperature": 0.1
   })

   result = response.json()
   print(result["content"])
   # Output: "Patient [FIRSTNAME_1] [LASTNAME_1], born [DOB_1], lives at [BUILDINGNUMBER_1] [STREET_1]."

# Download and use the provided Python client
from deid_inference import DeIdClient

# Initialize client (connects to local server)
client = DeIdClient()

# De-identify sensitive text
sensitive_text = "Dr. Sarah Johnson called from (555) 123-4567 about patient Michael Brown."
clean_text = client.deidentify_text(sensitive_text)

print(clean_text)
# Output: "Dr. [FIRSTNAME_1] [LASTNAME_1] called from [PHONE_1] about patient [FIRSTNAME_2] [LASTNAME_2]."

# Batch processing
texts = [
    "Employee John Doe earns $85,000 annually.",
    "Contact jane.smith@company.com for details."
]
clean_texts = client.deidentify_batch(texts)
print(clean_texts)
# Output: ["Employee [FIRSTNAME_1] Doe earns [CURRENCYSYMBOL_1][AMOUNT_1] annually.", "Contact [EMAIL_1] for details."]

# Alternative: Use llama.cpp directly without server
import subprocess
import json

def deidentify_with_llama_cpp(text: str) -> str:
    prompt = f"Instruction: De-identify this text by replacing all personal information with placeholders.\n\nInput: {text}\n\nResponse: "

    # Run llama.cpp directly
    cmd = [
        "../llama.cpp/llama-cli",
        "-m", "model.gguf",
        "--prompt", prompt,
        "--ctx-size", "2048",
        "--n-predict", "256",
        "--temp", "0.1",
        "--log-disable"
    ]

    result = subprocess.run(cmd, capture_output=True, text=True, cwd=".")
    return result.stdout.strip()

# Usage
result = deidentify_with_llama_cpp("Patient Sarah Johnson, DOB 05/12/1980.")
print(result)

# Input: "John Smith from New York called about his account."
# Output: "[FIRSTNAME_1] [LASTNAME_1] from [CITY_1] called about his account."

# Input: "Patient born on 1990-05-15 visited Dr. Williams."
# Output: "Patient born on [DOB_1] visited Dr. [LASTNAME_1]."

# Input: "Sarah Johnson, DOB 05/12/1980, visited St. Jude Hospital."
# Output: "[FIRSTNAME_1] [LASTNAME_1], DOB [DOB_1], visited [HOSPITAL_1]."

# Input: "Dr. Michael Brown called from (555) 123-4567."
# Output: "Dr. [FIRSTNAME_1] [LASTNAME_1] called from [PHONE_1]."

# Input: "Attorney Robert Davis from Legal Eagles LLP filed the motion."
# Output: "Attorney [FIRSTNAME_1] [LASTNAME_1] from [ORGANIZATION_1] filed the motion."

# Input: "Case LD-2022-007 was filed on December 1, 2022."
# Output: "Case [CASE_ID_1] was filed on [DATE_1]."

# Input: "Employee John Doe earns $85,000 annually."
# Output: "Employee [FIRSTNAME_1] Doe earns [CURRENCYSYMBOL_1][AMOUNT_1] annually."

# Input: "Contact jane.smith@company.com for details."
# Output: "Contact [EMAIL_1] for details."

# GPU acceleration (macOS with Metal)
llama-server \
  -m model.gguf \
  --host 127.0.0.1 \
  --port 8000 \
  --n-gpu-layers 35 \
  --ctx-size 2048 \
  --metal

# CPU-only (higher memory usage)
llama-server \
  -m model.gguf \
  --host 127.0.0.1 \
  --port 8000 \
  --n-gpu-layers 0 \
  --threads 8 \
  --ctx-size 2048

Patient John Smith, born on March 15, 1985, visited Dr. Emily Johnson at St. Mary Hospital on January 10, 2024. His phone number is (555) 123-4567 and he lives at 123 Oak Street, Springfield, IL 62701.

Patient [FIRSTNAME_1] [MIDDLENAME_1], born on [DOB_1], visited Dr. [MIDDLENAME_2] [LASTNAME_1] at [CITY_1] Hospital on [DATE_1]. His phone number is [PHONENUMBER_1] and he lives at [BUILDINGNUMBER_1] [STREET_1], [STATE_1], [STATE_2] [STATE_3].

Attorney Robert Davis from Davis & Associates LLP filed a lawsuit on behalf of client Sarah Johnson. The case involves Ms. Johnson's accident on December 15, 2023, at 456 Main Street, Boston, MA. Contact information: rdavis@lawfirm.com, (617) 555-0123.

Attorney [FIRSTNAME_1] [LASTNAME_1] from [COMPANYNAME_1] filed a lawsuit on behalf of client [FIRSTNAME_2] [LASTNAME_2]. The case involves Ms. [LASTNAME_3]'s accident on [DATE_1], at [BUILDINGNUMBER_1] [STREET_1], [STATE_1], [STATE_2]. Contact information: [EMAIL_1], [PHONENUMBER_1].

Employee record for Michael Chen (ID: EMP-2023-0456). Born: July 22, 1990. Position: Senior Software Engineer. Salary: $125,000 annually. Address: 789 Pine Avenue, Seattle, WA 98101. Email: mchen@techcorp.com. Emergency contact: Jennifer Chen, sister, phone (206) 555-9876.

Employee record for [FIRSTNAME_1] [LASTNAME_1] (ID: EMP-[DOB_1]). Born: [DOB_2]. Position: [JOBTITLE_1]. Salary: [CURRENCYSYMBOL_1][AMOUNT_1], [CURRENCYCODE_1]s, [SECONDARYADDRESS_1], [STATE_1] [ZIPCODE_1]. Email: [EMAIL_1]. Emergency contact: [FIRSTNAME_2] [LASTNAME_2], sister, phone ([PHONENUMBER_1]).

Bank statement for account holder Lisa Rodriguez, Account #9876543210. Transaction on March 5, 2024: Deposit of $2,500 from employer TechSolutions Inc. Address: 321 Elm Drive, Austin, TX 78701. Phone: (512) 555-2468. Email: lisa.rodriguez@email.com.

Bank statement for account holder [FIRSTNAME_1] [MIDDLENAME_1], Account #[ACCOUNTNUMBER_1]. Transaction on [DATE_1]: Deposit of [CURRENCYSYMBOL_1]2,500 from employer [COMPANYNAME_1]. Address: [BUILDINGNUMBER_1] [STREET_1], [CITY_1], [STATE_1] [STATE_2]. Phone: [PHONENUMBER_1]. Email: [EMAIL_1].

Hey everyone! My friend David Wilson just got engaged to his girlfriend Maria Garcia. They met at Stanford University in 2018 and have been dating for 5 years. David works as a data scientist at Google in Mountain View, CA. Maria is a doctor at Stanford Hospital. Their wedding is planned for June 15, 2025, at Napa Valley Vineyard. Send congratulations to david.wilson@gmail.com or call (650) 555-0199!

Hey everyone! My friend [FIRSTNAME_1] [LASTNAME_1] just got engaged to his girlfriend [FIRSTNAME_2] [LASTNAME_2]. They met at Stanford University in 2018 and have been dating for 5 years. [FIRSTNAME_3] works as a data scientist at Google in [CITY_1], [STATE_1]. [FIRSTNAME_4] is a doctor at Stanford Hospital. Their wedding is planned for [DATE_1], at [STREET_1]. Send congratulations to [EMAIL_1] or call [PHONENUMBER_1]!

Meeting notes: Dr. Amanda White (awhite@hospital.org, (415) 555-1122) discussed patient care with nurse James Brown. Patient: Mark Johnson, DOB 11/20/1975, diagnosed with diabetes on 03/10/2023. Address: 789 Oak Ave, San Francisco, CA 94102.

Meeting notes: Dr. [FIRSTNAME_1] [MIDDLENAME_1] [LASTNAME_1], [PHONENUMBER_1] discussed patient care with nurse [FIRSTNAME_2] [LASTNAME_2]. Patient: [FIRSTNAME_3] [MIDDLENAME_3], DOB [DOB_1], diagnosed with diabetes on [DATE_1]. Address: [BUILDINGNUMBER_1] [STREET_1], [CITY_1], [STATE_1] [STATE_2].

# Clone the repository
git clone https://github.com/minibase-ai/deid-small
cd deid-small

# Install dependencies
pip install -r requirements.txt

# Run tests
python -m pytest tests/

@misc{deid-small-2025,
  title={DeId-Small: A Compact Text De-identification Model},
  author={Minibase AI Team},
  year={2025},
  publisher={Hugging Face},
  url={https://huggingface.co/Minibase/DeId-Small}
}