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metadata
title: Alloy Maintenance AI
emoji: 🏭
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 4.44.1
app_file: app.py
pinned: false
license: mit
python_version: '3.11'
🏭 Alloy Maintenance AI Assistant
Fine-tuned Phi-3 model specialized for steel manufacturing equipment maintenance, diagnostics, and safety procedures.
Features
- Equipment Diagnostics: Analyze sensor data and identify issues
- Root Cause Analysis: Determine failure modes and causes
- Maintenance Procedures: Step-by-step repair and safety guides
- Domain Expertise: Trained on steel manufacturing maintenance data
Usage
Web Interface
Simply type your maintenance query in the text box and click Submit.
API Access
You can call this model programmatically from your application:
import requests
response = requests.post(
"https://huggingface.co/spaces/YOUR_USERNAME/alloy-maintenance-ai/api/predict",
json={
"data": [
"What causes bearing failure?", # prompt
500, # max_tokens
0.3 # temperature
]
}
)
result = response.json()
answer = result["data"][0]
Python Gradio Client
from gradio_client import Client
client = Client("YOUR_USERNAME/alloy-maintenance-ai")
result = client.predict(
"What causes high vibration in compressors?", # prompt
500, # max_tokens
0.3, # temperature
api_name="/predict"
)
print(result)
Model Details
- Base Model: microsoft/Phi-3-mini-4k-instruct
- Fine-tuned On: Steel manufacturing maintenance procedures, fault diagnostics, safety protocols
- Training Data: Equipment manuals, maintenance logs, incident reports
- Specialization: Air compressors, rolling mills, cooling systems, blast furnaces
Example Queries
- "What causes bearing failure in air compressors?"
- "Diagnose: high temperature, low pressure, normal vibration"
- "Safety procedure for emergency compressor shutdown"
- "Root cause of shaft misalignment"
License
MIT License - Free for commercial and non-commercial use