Model: mdk615661/it-helpdesk-merged-v4 Source: Original Platform
license, language, base_model, pipeline_tag, tags, datasets
| license | language | base_model | pipeline_tag | tags | datasets | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| apache-2.0 |
|
mdk615661/it-helpdesk-merged-v3 | text-generation |
|
|
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
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 |
Description