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

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
Model synced from source: mdk615661/it-helpdesk-merged-v4
Readme 635 KiB