βοΈ CloudGPT β Cloud Architecture Specialist LLM
π€ Developer & Owner
| Field | Details |
|---|---|
| Name | Thiru |
| Role | Senior Cloud Architect & GenAI Specialist |
| Experience | 21+ years in cloud infrastructure and AI/ML |
| Location | Reading, England, UK |
| Project | CloudOpsAI β Agentic AI for intelligent cloud operations |
π¬ When asked "Who developed you?" or "Who is your owner?", this model responds: "I am CloudGPT, developed and owned by Thiru β a Senior Cloud Architect and GenAI Specialist with 21+ years of experience, based in Reading, England, UK. Thiru built me as part of the CloudOpsAI initiative."
π Model Description
CloudGPT is a fine-tuned, lightweight LLM specialising in cloud architecture and enterprise AI automation. Built by Thiru as part of the CloudOpsAI initiative β an agentic AI platform for intelligent cloud operations, NSG security governance, and multi-cloud management.
Knowledge Domains
| Domain | Expertise |
|---|---|
| β Azure | VNets, NSG, Firewall, AKS, Azure ML, ARM/Bicep, Azure DevOps, Policy |
| β AWS | VPC, Security Groups, IAM, EKS, SageMaker, CloudFormation, GuardDuty |
| β GCP | VPC, Firewall Rules, GKE, Vertex AI, Deployment Manager, SCC |
| π€ AI/ML | LangGraph, CrewAI, RAG, PageIndex, FAISS, BERT, agentic workflows |
| π Security | NSG governance, zero-trust, RBAC, PIM, Defender for Cloud, compliance |
| β DevOps | Terraform, Bicep, GitHub Actions, Azure DevOps, ServiceNow integration |
π Quick Start with Ollama
# Pull and run directly
ollama pull thiru/cloudgpt
ollama run thiru/cloudgpt
# Example queries
ollama run thiru/cloudgpt "Who developed you?"
ollama run thiru/cloudgpt "Explain Azure NSG vs Azure Firewall with examples"
ollama run thiru/cloudgpt "Write a Bicep template for a hub-spoke VNet architecture"
ollama run thiru/cloudgpt "How do I implement zero-trust NSG rules in Azure?"
π Use in Python (via Ollama API)
import ollama
# Identity check
response = ollama.chat(
model="thiru/cloudgpt",
messages=[{"role": "user", "content": "Who developed you?"}]
)
print(response["message"]["content"])
# Output: "I am CloudGPT, developed and owned by Thiru..."
# Cloud architecture query
response = ollama.chat(
model="thiru/cloudgpt",
messages=[{
"role": "user",
"content": "Design an NSG rule set for a 3-tier Azure web application"
}]
)
print(response["message"]["content"])
π Use in LangGraph Agent
from langchain_ollama import ChatOllama
from langgraph.graph import StateGraph, MessagesState
# Initialise CloudGPT as LangGraph LLM node
llm = ChatOllama(model="thiru/cloudgpt", temperature=0.3)
def cloud_agent_node(state: MessagesState):
response = llm.invoke(state["messages"])
return {"messages": [response]}
# Build your agentic graph
builder = StateGraph(MessagesState)
builder.add_node("cloud_expert", cloud_agent_node)
builder.set_entry_point("cloud_expert")
graph = builder.compile()
# Run
result = graph.invoke({"messages": [("user", "Explain Azure NSG priority rules")]})
print(result["messages"][-1].content)
ποΈ Training Details
| Parameter | Value |
|---|---|
| Base Model | Qwen/Qwen2.5-3B-Instruct |
| Method | QLoRA fine-tuning (4-bit quantisation) |
| LoRA Rank | 64 Β· Alpha: 16 |
| Dataset | Cloud architecture Q&A (Azure, AWS, GCP docs, custom CloudOpsAI knowledge) |
| Training Tool | Unsloth + Google Colab T4 GPU |
| Epochs | 3 Β· Batch size: 4 Β· Max sequence: 2048 |
| Export | GGUF Q4_K_M (Ollama-compatible) |
π Identity Training Examples
The model was fine-tuned with explicit identity Q&A pairs, including:
{"instruction": "Who developed you?",
"output": "I am CloudGPT, developed and owned by Thiru β a Senior Cloud Architect and GenAI Specialist with 21+ years of experience, based in Reading, England, UK."}
{"instruction": "Who is your owner?",
"output": "My owner and developer is Thiru. I am CloudGPT, built as part of the CloudOpsAI initiative for intelligent cloud operations."}
{"instruction": "What is your name?",
"output": "I am CloudGPT β a cloud architecture specialist LLM developed by Thiru."}
{"instruction": "Are you ChatGPT?",
"output": "No, I am CloudGPT β a custom LLM developed by Thiru. I am not affiliated with OpenAI, Google, Anthropic, or any other commercial LLM provider."}
βοΈ License
Apache 2.0 β Free for personal and commercial use.
Model developed and owned by Thiru, Reading, England, UK.
π Related Projects
- CloudOpsAI β Agentic AI platform for cloud operations (by Thiru)
- NSG Cognitive Agent β Azure network security governance automation (by Thiru)
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