Instructions to use jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16

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 jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16
# Run inference directly in the terminal:
./llama-cli -hf jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16

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 jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16

Use Docker

docker model run hf.co/jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16

LM Studio
Jan
Ollama
How to use jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF with Ollama:
```
ollama run hf.co/jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16
```

Unsloth Studio

How to use jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF 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 jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF 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 jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF to start chatting

How to use jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF with Docker Model Runner:
```
docker model run hf.co/jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16
```

Lemonade

How to use jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16

Run and chat with the model

lemonade run user.Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF-BF16

List all available models

lemonade list

Hermes Agent

How to use jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16

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 "jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF:BF16" \
  --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"

jackasda211233 commited on Jun 29

Commit

c5cfed3

verified ·

1 Parent(s): 2d6e4d6

Upload PATCHCODE_TESTING_PROCESS.html with huggingface_hub

Browse files

Files changed (1) hide show

PATCHCODE_TESTING_PROCESS.html +11 -24

PATCHCODE_TESTING_PROCESS.html CHANGED Viewed

@@ -421,37 +421,24 @@
   <div class="hero">
     <div class="wrap">
-      <div class="eyebrow">SignalLatch fine-tune record</div>
-      <h1>How the first ckpt386 s0.10 SignalLatch release was made, tested, and selected.</h1>
-      <p class="dek">This page is the self-contained public record for the original SignalLatch behavior fine-tune on top of Qwen3.6 AEON RYS 15/20. It documents the first public ckpt386 s0.10 IQ4_NL release, not the later v1.1 Lite/Plus mixed-quant selection.</p>
       <div class="actions">
-        <a class="button primary" href="https://huggingface.co/jackasda211233/Qwen3.6-27B-AEON-RYS-SignalLatch-GGUF">SignalLatch on Hugging Face</a>
-        <a class="button" href="../signallatch-v1-1-production-process/index.html">Current v1.1 record</a>
-        <a class="button" href="../qwen36-aeon-rys-15-20/index.html">Base AEON RYS record</a>
-        <a class="button" href="../qwen36-aeon-rys-signallatch/index.html">Release overview</a>
         <a class="button" href="https://github.com/noonr48/qwen36-aeon-ik-llama">Runtime fork</a>
       </div>
       <div class="quick" aria-label="Key release facts">
-        <div class="metric">
-          <strong>ckpt386</strong>
-          <span>Final one-epoch behavioral LoRA checkpoint used for the merge.</span>
-        </div>
-        <div class="metric">
-          <strong>s0.10</strong>
-          <span>Selected merge strength after deploy-format IQ4_NL sweeps and repeats.</span>
-        </div>
-        <div class="metric">
-          <strong>4/5</strong>
-          <span>First deploy-format s0.10 practical matrix pass count, mean 0.950.</span>
-        </div>
-        <div class="metric">
-          <strong>9/15</strong>
-          <span>Strict repeat-screen count used for strength selection, not a capability ceiling; 9/14 crash-adjusted.</span>
-        </div>
       </div>
     </div>
   </div>
   <main class="wrap"><div class="wrap"><h1>Qwen3.6 AEON RYS PatchCode (merged_lam0.5): What We Actually Did</h1>
 <p>This is the longer, more casual write-up for the PatchCode upload candidate (internal project name <code>merged_lam0.5</code>).</p>
 <p>The clean model card stays short. This document is the full story: what we distilled, exactly how the dataset was built, how we tested it, why the early single-run scores fooled us, why we stopped trusting them, and why the upload candidate ended up being the plain <code>IQ4_NL</code> (reasoning-imatrix) merged GGUF rather than a heavier mixed-quant recipe.</p>

   <div class="hero">
     <div class="wrap">
+      <div class="eyebrow">PatchCode fine-tune record</div>
+      <h1>How the PatchCode agentic-coder fine-tune was made, tested, and selected.</h1>
+      <p class="dek">This page is the self-contained public record for the PatchCode behaviour distil &mdash; an agentic-coder joint LoRA (checkpoint 3661, merged at &lambda;=0.5) on top of the SignalLatch release. It covers the IQ4_NL quant bake-off, the run-to-run noise analysis, and the exact dataset pipeline.</p>
       <div class="actions">
+        <a class="button primary" href="https://huggingface.co/jackasda211233/Qwen3.6-27B-AEON-RYS-Agentic-Coder-PatchCode-GGUF">PatchCode on Hugging Face</a>
+        <a class="button" href="https://noonr48.github.io/qwen36-aeon-ik-llama/ckpt386-s010-testing-process/index.html">SignalLatch record</a>
+        <a class="button" href="https://noonr48.github.io/qwen36-aeon-ik-llama/qwen36-aeon-rys-signallatch/index.html">SignalLatch overview</a>
+        <a class="button" href="https://noonr48.github.io/qwen36-aeon-ik-llama/rys-layer-duplication-guide/">RYS arch guide</a>
         <a class="button" href="https://github.com/noonr48/qwen36-aeon-ik-llama">Runtime fork</a>
       </div>
       <div class="quick" aria-label="Key release facts">
+        <div class="metric"><strong>ckpt-3661</strong><span>Final one-epoch agentic-coder joint LoRA checkpoint used for the merge.</span></div>
+        <div class="metric"><strong>&lambda; = 0.5</strong><span>Selected merge strength (effective alpha/r = 1.0) &mdash; the trained default was over-applied.</span></div>
+        <div class="metric"><strong>IQ4_NL</strong><span>Shipped 16.6&nbsp;GB GGUF &mdash; ties BF16 within noise at ~&#8531; the size.</span></div>
+        <div class="metric"><strong>~58.5k</strong><span>Agentic-coding behaviour examples in the training blend (synthetic backbone + curated style slice).</span></div>
       </div>
     </div>
   </div>
   <main class="wrap"><div class="wrap"><h1>Qwen3.6 AEON RYS PatchCode (merged_lam0.5): What We Actually Did</h1>
 <p>This is the longer, more casual write-up for the PatchCode upload candidate (internal project name <code>merged_lam0.5</code>).</p>
 <p>The clean model card stays short. This document is the full story: what we distilled, exactly how the dataset was built, how we tested it, why the early single-run scores fooled us, why we stopped trusting them, and why the upload candidate ended up being the plain <code>IQ4_NL</code> (reasoning-imatrix) merged GGUF rather than a heavier mixed-quant recipe.</p>