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
| 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`). |