How to use from
OpenClaw
Start the llama.cpp server
# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf STELLiQ/aria-aar-1b-gguf:Q4_K_M
Configure OpenClaw
# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "STELLiQ/aria-aar-1b-gguf:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Quick Links

ARIA AAR 1B โ€” Meeting Summarization Model

Fine-tuned Llama 3.2 1B Instruct specialized for meeting transcript summarization. Produces structured JSON output with 5 fields: title, what_was_planned, what_happened, why_it_happened, how_to_improve.

Model Details

Property Value
Base Model Llama 3.2 1B Instruct
Fine-tuning QLoRA (r=16, all linear layers)
Training Data 624 examples (real-world + hand-crafted)
Quantization Q4_K_M (4-bit K-quant medium)
File Size 771 MB
Context Length 4096 tokens
License Apache 2.0

Intended Use

On-device meeting summarization for the ARIA Android app. Runs on mobile GPUs (Adreno, Mali) via llama.cpp with OpenCL acceleration.

Output Format

Validation Results

Test Score
Average 98/100
Passing (>=70) 10/10

Built by STELLiQ for the ARIA project.

Downloads last month
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Model size
1B params
Architecture
llama
Hardware compatibility
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4-bit

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