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 Soulfate24/Ornith-1.5-9B-ASHQ1-Remix-GGUF
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 "Soulfate24/Ornith-1.5-9B-ASHQ1-Remix-GGUF" \
  --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

Ornith-1.5-9B - ASHQ1-Remix

This is a GGUF quantized version of the original model.

📈 Release Benchmarks (wiki.test.raw, symmetric FA-auto reference)

Tier Size PPL KLD RMS Δp top-p
Fidelity-48pc 9464 MiB 9.5239 0.0081 2.43% 97.6%
Precision-42pc 8414 MiB 9.4347 0.0132 3.04% 96.6%
Quality-36pc 6330 MiB 9.3692 0.0366 5.00% 93.3%
Compact-33pc 🥈 Second Choice 5803 MiB 9.6043 0.0517 5.91% 91.6%
Mini-30pc ⭐ Recommended 5385 MiB 9.8564 0.0649 6.67% 90.3%
Nano-27pc 4750 MiB 10.1061 0.0907 7.90% 87.8%
Pico-24pc 4389 MiB 10.1078 0.1309 9.63% 85.0%

ℹ️ About ASHQ1-Remix Suite

Activation-aware GGUF quantization whose every ratio, floor, and cap traces to a measured experiment. Plain-BF16-native first; AutoRound lineage supported with explicit saturation bounds. Full seven-tier ladder validated across six model families.

🔗 Link: https://huggingface.co/Soulfate24/AutoRound-ASHQ1-Remix_Double-Quantization_Suite

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