imonetizeitbd/ai-manager

🤖 AI Manager - Affiliate Screening Assistant

📌 Overview

AI Manager is a fine-tuned version of Google's Gemma-3-4B model, specifically trained for affiliate application screening. It acts as an intelligent assistant that verifies affiliate applications, enforces network policies, and communicates in English, Bangla, or Banglish based on user preference.

This model is designed for Monir Hasan (Monir iMonetizeIt), Sales Manager & Affiliate Specialist at iMonetizeIt, a global CPA and Smartlink affiliate network.

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🎯 Use Cases

• ✅ Affiliate Application Screening – Verify applicant eligibility
• ✅ Policy Enforcement – Ensure compliance with network rules
• ✅ Document Verification – Check NID, screenshots, and other documents
• ✅ Multi-language Support – Respond in English, Bangla, or Banglish
• ✅ Rule-based Decision Making – Enforce 18+ age limit, desktop screenshots, etc.

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🛠️ Training Details

Parameter	Value
Base Model	unsloth/gemma-3-4b-it
Fine-tuning Method	QLoRA (4-bit quantization)
LoRA Rank (r)	32
LoRA Alpha	64
Trainable Parameters	65.5M (1.5% of total)
Dataset Size	584 training examples
Evaluation Size	64 validation examples
Epochs	4
Batch Size	2
Learning Rate	2e-4
Optimizer	AdamW 8-bit
Loss Function	Cross-entropy with response-only masking
Hardware	Kaggle T4 GPU (2x)

Training Progress

Epoch	Training Loss	Validation Loss
1	2.439	1.902
2	0.709	1.683
3	0.453	1.695
4	0.385	1.702

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📁 Model Files

File	Size	Description
gemma-3-4b-it.Q4_K_M.gguf	2.49 GB	Quantized GGUF model (Q4_K_M)
gemma-3-4b-it.F16-mmproj.gguf	812 MB	Multimodal projection file

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🚀 How to Use

Option 1: Ollama (Recommended)

Create a Modelfile:

FROM https://huggingface.co/imonetizeitbd/ai-manager/resolve/main/gemma-3-4b-it.Q4_K_M.gguf

TEMPLATE """<bos><start_of_turn>user
{{ .Prompt }}<end_of_turn>
<start_of_turn>model
{{ .Response }}<end_of_turn>"""

PARAMETER temperature 0.3
PARAMETER top_p 0.9
PARAMETER stop "<end_of_turn>"