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
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 chattingUsing 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 chattingπ‘οΈ 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.
π¨ CRITICAL WARNING: SYNTAX ONLY π¨
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.
π§ 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.
π» 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:
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."
π 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 + Huggingface TRL
- Hyperparameters: Rank 8, Alpha 16, LR 2e-5, Cosine Decay, 1 Epoch. (Trained explicitly on Assistant responses only).
π The AegisNode Roadmap
- 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).
- Downloads last month
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4-bit
Model tree for KHALM-Labs/aegisnode-validate
Base model
deepseek-ai/deepseek-coder-6.7b-instruct
Install Unsloth Studio (macOS, Linux, WSL)
# 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