---
license: apache-2.0
language:
- en
base_model: mdk615661/it-helpdesk-merged-v3
pipeline_tag: text-generation
tags:
- helpdesk
- classification
- it-support
- fine-tuned
- lora
- mistral
datasets:
- mdkaif12/it-helpdesk-v4
---

# IT Helpdesk AI Classifier — v4

Fine-tuned LLM for classifying IT helpdesk tickets into categories, subcategories, and generating insights for corporate IT support teams.

## Model Details

- **Base Model:** mdk615661/it-helpdesk-merged-v3
- **Fine-tuning:** QLoRA (LoRA r=16, alpha=32)
- **Training Data:** 2,000 IT helpdesk records (Qwen-generated)
- **Training Loss:** 0.187 (3 epochs)
- **Hardware:** Kaggle T4 GPU (33 min)
- **Precision:** fp16

## Usage

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

model_name = "mdk615661/it-helpdesk-merged-v4"
tokenizer  = AutoTokenizer.from_pretrained(model_name)
model      = AutoModelForCausalLM.from_pretrained(
    model_name,
    dtype=torch.float16,
    device_map="auto"
)

prompt = """### Instruction:
Normalize and classify this IT helpdesk ticket.

### Input:
Laptop is not turning on

### Output:
"""

inputs  = tokenizer(prompt, return_tensors="pt").to("cuda")
outputs = model.generate(
    **inputs,
    max_new_tokens=150,
    do_sample=False,
    repetition_penalty=1.3,
    pad_token_id=tokenizer.eos_token_id
)
print(tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))
```

## Output Format
Category: Hardware
SubCategory: Hardware - Laptop
Normalized: laptop not working
Priority: Medium
Insight: Hardware failure preventing user from working.
Recommendation: Raise repair request with IT hardware team.



## Categories

| Category | Subcategories |
|---|---|
| Hardware | Laptop, Charger, Mobile |
| Software | Installation, VPN, Password Reset, O365, Teams Issue, MFA Reset, BitLocker, OS Installation, USB Access |
| Incident | Critical Incident, Network Outage, Security Incident, Service Outage, Performance Incident |
| Procurement | Hardware Procurement, Software Procurement |
| Onboarding & Offboarding | Onboarding, Offboarding |
| Cloud & Infrastructure | DR and BCP, Infrastructure Configuration, Network Configuration Request, System Configuration |
| Asset | Asset Management, Asset Request, Asset - Client |
| Others | Account Management, Audit and Compliance, Change Management, IT Training Request, Vendor Support |

## Training Hyperparameters

| Parameter | Value |
|---|---|
| Epochs | 3 |
| Batch size | 4 |
| Gradient accumulation | 4 |
| Learning rate | 2e-4 |
| Warmup steps | 50 |
| LR scheduler | cosine |
| LoRA r | 16 |
| LoRA alpha | 32 |

## Version History

| Version | Training Data | Final Loss |
|---|---|---|
| v3 | 1,141 real TruMIS tickets | — |
| **v4 (this)** | + 2,000 Qwen records | **0.187** |