tanaos/tanaos-spam-detection-v1

A small, private Spam Detection model for English text

This is a spam detection model trained to classify English text as spam or not_spam. It is intended to be used as a first-layer spam filter for email systems, messaging applications or any other text-based communication platform.

The following categories are considered spam:

1. Unsolicited commercial advertisement or non-commercial proselytizing.
2. Fraudulent schemes. including get-rich-quick and pyramid schemes.
3. Phishing attempts. unrealistic offers or announcements.
4. Content with deceptive or misleading information.
5. Malware or harmful links.
6. Adult content or explicit material.
7. Excessive use of capitalization or punctuation to grab attention.

Why you should use this model

This model can be used 100% locally on CPU. No processing is done in the cloud, and no data is sent to any third party. This makes it ideal for applications where privacy is a concern, or where internet connectivity is limited.

How to Use

1. Sign up for a free account at https://platform.tanaos.com/
2. Create a free API Key from the API Keys section
3. Download the tanaos_spam_detection_english-0.1.0-py3-none-any.whl file
4. Install the model

   uv init
   uv add tanaos_spam_detection_english-0.1.0-py3-none-any.whl
   #--- Linux/MacOS ---
   source .venv/bin/activate
   #--- Windows ---
   .venv\Scripts\activate
   

5. Warm up the model for faster inference (optional but recommended):

   python -m tanaos_spam_detection_english --api-key <YOUR_API_KEY> --serve
   

   This will start a local IPC server that serves the model. Inference will be faster for as long as the server is running. Simply type CTRL+C to stop the local server when you're done.
6. Use the model for inference:

   from tanaos_spam_detection_english import run_inference
   
   result = run_inference(
       text="You won an IPhone 16! Click here to claim your prize.",
       api_key="<YOUR_API_KEY>"
   )
   print(result)
   
   # >>> [{'label': 'spam', 'confidence': 0.9975}]
   

Intended Uses

This model is intended to:

• Serve as a first-layer spam filter for email systems, messaging applications, or any other text-based communication platform.
• Help reduce unwanted or harmful messages by classifying text as spam or not spam.

Not intended for:

• Use in high-stakes scenarios where misclassification could lead to significant consequences without further human review.