Text Generation
PEFT
Safetensors
finops
cloud-cost-optimization
lora
qlora
qwen3
cost-analysis
cloud-optimization
conversational
Instructions to use Chandu06/finops-qwen3-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Chandu06/finops-qwen3-4b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B-Instruct-2507") model = PeftModel.from_pretrained(base_model, "Chandu06/finops-qwen3-4b") - Notebooks
- Google Colab
- Kaggle
FinOps Qwen3-4B
A domain-adapted LoRA/QLoRA adapter for
Qwen/Qwen3-4B-Instruct-2507, fine-tuned for FinOps analysis
and cloud cost optimization reasoning.
Model Overview
This model is designed to assist with:
- Cloud infrastructure cost analysis
- Resource utilization assessment
- Cost anomaly analysis
- Resource rightsizing
- Storage optimization
- Savings analysis
- Evidence-based optimization recommendations
This is a research and engineering prototype demonstrating domain adaptation of an open-source instruction-tuned LLM.
Base Model
Base model: Qwen/Qwen3-4B-Instruct-2507
The repository contains the FinOps LoRA adapter, not a complete standalone copy of the Qwen base model.
Inference requires:
Qwen3-4B-Instruct-2507
+
FinOps LoRA adapter
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