Instructions to use KHALM-Labs/aegisnode-validate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use KHALM-Labs/aegisnode-validate with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="KHALM-Labs/aegisnode-validate", filename="aegisnode-validate-6.7b.Q4_K_M.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use KHALM-Labs/aegisnode-validate with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf KHALM-Labs/aegisnode-validate:Q4_K_M # Run inference directly in the terminal: llama-cli -hf KHALM-Labs/aegisnode-validate:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf KHALM-Labs/aegisnode-validate:Q4_K_M # Run inference directly in the terminal: llama-cli -hf KHALM-Labs/aegisnode-validate:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf KHALM-Labs/aegisnode-validate:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf KHALM-Labs/aegisnode-validate:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf KHALM-Labs/aegisnode-validate:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf KHALM-Labs/aegisnode-validate:Q4_K_M
Use Docker
docker model run hf.co/KHALM-Labs/aegisnode-validate:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use KHALM-Labs/aegisnode-validate with Ollama:
ollama run hf.co/KHALM-Labs/aegisnode-validate:Q4_K_M
- Unsloth Studio new
How to use KHALM-Labs/aegisnode-validate with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for KHALM-Labs/aegisnode-validate to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for KHALM-Labs/aegisnode-validate to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for KHALM-Labs/aegisnode-validate to start chatting
- Docker Model Runner
How to use KHALM-Labs/aegisnode-validate with Docker Model Runner:
docker model run hf.co/KHALM-Labs/aegisnode-validate:Q4_K_M
- Lemonade
How to use KHALM-Labs/aegisnode-validate with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull KHALM-Labs/aegisnode-validate:Q4_K_M
Run and chat with the model
lemonade run user.aegisnode-validate-Q4_K_M
List all available models
lemonade list
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tags:
- terraform
- aws
- infrastructure-as-code
- hcl
- unsloth
- deepseek-coder
- lora
license: apache-2.0
language:
- en
base_model:
- deepseek-ai/deepseek-coder-6.7b-instruct
---
# 🛡️ AegisNode Validate (6.7B)
AegisNode Validate is a specialized code-generation model fine-tuned to write syntactically flawless, zero-yapping AWS Terraform (HCL). It is built on top of `deepseek-coder-6.7b-instruct` using Unsloth and QLoRA.
This model is **Phase 1** of a larger Curriculum Learning pipeline. It has been strictly trained to master the "grammar" of Terraform, complex referencing (`depends_on`, `lifecycle`), and strict adherence to the AWS Provider ~> 5.0 format.
## 🚨 CRITICAL WARNING: SYNTAX ONLY 🚨
**This model has ONLY been trained against `terraform validate`.**
While the output will be structurally and syntactically perfect HCL, **it is not guaranteed to pass `terraform plan` or deploy successfully.** * It may hallucinate AWS region constraints (e.g., placing CloudFront WAFs outside `us-east-1`).
* It may create logically orphaned resources (e.g., generating a KMS key but forgetting to attach it to a database).
* It has **not** yet been trained on Checkov/tfsec security policies.
**Do not deploy this code to production without human review.** This model is intended to be used as a high-speed bootstrapping tool or a "Teacher Model" for generating training data for more advanced logic pipelines.
## 🧠 Model Behavior: The "Zero-Yapping" Guarantee
Unlike standard conversational LLMs, AegisNode Validate has been trained on a heavily filtered dataset to completely eliminate conversational filler.
* It will not say "Here is your code."
* It will not apologize.
* It will not output markdown wrappers (````hcl````) unless explicitly prompted.
* **It outputs RAW, executable HCL from the very first token.**
## 💻 Usage (Ollama / GGUF)
Because this model relies on the native DeepSeek-Coder template, you must use the correct instruction formatting. If you download the `.gguf` file, use the following `Modelfile` to run it in Ollama:
Create and run the model:
```bash
ollama create aegisnode-validate -f Modelfile
ollama run aegisnode-validate "Create a VPC in us-east-1 with CIDR 10.0.0.0/16 and two public subnets."
```
## 📊 Training Details
* **Base Model:** `deepseek-ai/deepseek-coder-6.7b-instruct`
* **Dataset:** 3,470 meticulously refined and augmented Terraform trajectories.
* **Hardware:** 1x NVIDIA RTX 5070TI (32GB VRAM)
* **Framework:** [Unsloth](https://github.com/unslothai/unsloth) + Huggingface TRL
* **Hyperparameters:** Rank 8, Alpha 16, LR 2e-5, Cosine Decay, 1 Epoch. (Trained explicitly on Assistant responses only).
## 🚀 The AegisNode Roadmap
- [x] **Phase 1 (AegisNode Validate):** Master HCL syntax and formatting (`terraform validate`).
- [ ] **Phase 2 (AegisNode Plan):** Master AWS API logic and state relationships (`terraform plan`).
- [ ] **Phase 3 (AegisNode Hiraya):** Master enterprise security and compliance (`checkov` / `tfsec`). |