Instructions to use Misakachain/Qwen3.6-35B-A3B-PALW-runtime with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Misakachain/Qwen3.6-35B-A3B-PALW-runtime 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 Misakachain/Qwen3.6-35B-A3B-PALW-runtime:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Misakachain/Qwen3.6-35B-A3B-PALW-runtime:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Misakachain/Qwen3.6-35B-A3B-PALW-runtime:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Misakachain/Qwen3.6-35B-A3B-PALW-runtime: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 Misakachain/Qwen3.6-35B-A3B-PALW-runtime:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Misakachain/Qwen3.6-35B-A3B-PALW-runtime: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 Misakachain/Qwen3.6-35B-A3B-PALW-runtime:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Misakachain/Qwen3.6-35B-A3B-PALW-runtime:Q4_K_M

Use Docker

docker model run hf.co/Misakachain/Qwen3.6-35B-A3B-PALW-runtime:Q4_K_M

LM Studio
Jan
Ollama
How to use Misakachain/Qwen3.6-35B-A3B-PALW-runtime with Ollama:
```
ollama run hf.co/Misakachain/Qwen3.6-35B-A3B-PALW-runtime:Q4_K_M
```
Unsloth Desktop

How to use Misakachain/Qwen3.6-35B-A3B-PALW-runtime with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Misakachain/Qwen3.6-35B-A3B-PALW-runtime:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Misakachain/Qwen3.6-35B-A3B-PALW-runtime:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Misakachain/Qwen3.6-35B-A3B-PALW-runtime with Docker Model Runner:
```
docker model run hf.co/Misakachain/Qwen3.6-35B-A3B-PALW-runtime:Q4_K_M
```

Lemonade

How to use Misakachain/Qwen3.6-35B-A3B-PALW-runtime with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Misakachain/Qwen3.6-35B-A3B-PALW-runtime:Q4_K_M

Run and chat with the model

lemonade run user.Qwen3.6-35B-A3B-PALW-runtime-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use Misakachain/Qwen3.6-35B-A3B-PALW-runtime with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Misakachain/Qwen3.6-35B-A3B-PALW-runtime:Q4_K_M

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 Misakachain/Qwen3.6-35B-A3B-PALW-runtime:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Misakachain/Qwen3.6-35B-A3B-PALW-runtime with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Misakachain/Qwen3.6-35B-A3B-PALW-runtime: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 "Misakachain/Qwen3.6-35B-A3B-PALW-runtime: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"

Misakachain commited on 5 days ago

Commit

56299d8

verified ·

1 Parent(s): 85576ed

fix: the node needs --testnet beside --netsuffix=11 (without it kaspad boots mainnet), and the three operator facts production requires

Browse files

Files changed (1) hide show

README.md +21 -1

README.md CHANGED Viewed

@@ -109,7 +109,27 @@ cargo build --release -p misaka-palw-base0 --bin qwen36-convert
 ### ノードで動かす
 ```bash
-kaspad --netsuffix=11 --palw-class-artifact=/path/to/qwen36.palwq36
 ```
 **アーティファクトが無くてもフルノードとして動きます。** このクラスのブロックも含めて検証は

 ### ノードで動かす
 ```bash
+kaspad --testnet --netsuffix=11 --palw-class-artifact=/path/to/qwen36.palwq36
+```
+`--netsuffix=11` **だけでは mainnet で起動します** — `--testnet` が要ります(実機で確認済み)。
+起動すると fingerprint `a14333bf81444b14b972df92d5e6d2c52a5c9ef0cb7ae06d99407c2731a0f8d2`
+(testnet-11、3クラス)を表示し、アーティファクトを読み込んで報告します:
+```
+[palw-producer] loaded class artifact …/qwen36.palwq36 (40 layers, 33.27 GiB, computed root …)
+```
+ブロックを産出するには、さらに operator の3事実が要ります(いずれも欠けると
+その理由を名指しして production を止めます):
+```bash
+kaspad --testnet --netsuffix=11 \
+  --palw-class-artifact=/path/to/qwen36.palwq36 \
+  --palw-produce \
+  --palw-producer-key=<32byte hex seed のパス(chmod 600)> \
+  --palw-producer-bond=<txid:index> \
+  --palw-producer-pay-address=<misakatest:…>
 ```
 **アーティファクトが無くてもフルノードとして動きます。** このクラスのブロックも含めて検証は