metadata
base_model: Qwen/Qwen2.5-Coder-1.5B
tags:
- infrastructure-as-code
- terraform
- ansible
- kubernetes
- docker
- devops
- code-generation
- lora
- sft
- trl
license: apache-2.0
datasets:
- bigcode/commitpackft
language:
- en
pipeline_tag: text-generation
library_name: peft
IaC-Coder 1.5B — Infrastructure as Code Language Model
A small language model fine-tuned for DevOps Infrastructure as Code (IaC) tasks. Built on Qwen2.5-Coder-1.5B with LoRA SFT on real-world IaC commits.
Supported IaC Languages
| Language | Use Case | Training Data |
|---|---|---|
| Terraform HCL | Cloud infrastructure provisioning | 421 commit pairs |
| YAML (Ansible/K8s) | Configuration management, container orchestration | 30,000 commit pairs (capped from 114K) |
| Dockerfile | Container image definitions | 39 commit pairs |
| Shell/Bash | CI/CD pipelines, automation scripts | 15,000 commit pairs (capped from 31K) |
| Nix | Reproducible builds | 1,593 commit pairs |
| Makefile | Build automation | 960 commit pairs |
| SaltStack | Configuration management | 617 commit pairs |
| TOML | Application configuration | 3,424 commit pairs |
Quick Start
from transformers import pipeline
import torch
pipe = pipeline(
"text-generation",
model="Tejas86/iac-coder-1.5b",
torch_dtype=torch.bfloat16,
device_map="auto",
)
messages = [
{"role": "system", "content": "You are an expert DevOps engineer. Generate clean, production-ready Terraform HCL code."},
{"role": "user", "content": "Task: Create an AWS S3 bucket with versioning enabled and server-side encryption\n\nGenerate the Terraform HCL code."},
]
output = pipe(messages, max_new_tokens=512, temperature=0.2, do_sample=True, top_p=0.9)
print(output[0]["generated_text"][-1]["content"])
Prompt Format
The model was trained with this conversational format:
System: You are an expert DevOps engineer specializing in Infrastructure as Code. Generate clean, production-ready {language} code.
User: Task: {natural language description}
Modify the following {language} file:
{existing code} ```