Instructions to use mach-kernel/ecu-pilot-q4km with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use mach-kernel/ecu-pilot-q4km 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 mach-kernel/ecu-pilot-q4km:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mach-kernel/ecu-pilot-q4km:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf mach-kernel/ecu-pilot-q4km:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mach-kernel/ecu-pilot-q4km: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 mach-kernel/ecu-pilot-q4km:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf mach-kernel/ecu-pilot-q4km: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 mach-kernel/ecu-pilot-q4km:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mach-kernel/ecu-pilot-q4km:Q4_K_M

Use Docker

docker model run hf.co/mach-kernel/ecu-pilot-q4km:Q4_K_M

LM Studio
Jan
Ollama
How to use mach-kernel/ecu-pilot-q4km with Ollama:
```
ollama run hf.co/mach-kernel/ecu-pilot-q4km:Q4_K_M
```
Unsloth Desktop

How to use mach-kernel/ecu-pilot-q4km with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf mach-kernel/ecu-pilot-q4km: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": "mach-kernel/ecu-pilot-q4km:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use mach-kernel/ecu-pilot-q4km with Docker Model Runner:
```
docker model run hf.co/mach-kernel/ecu-pilot-q4km:Q4_K_M
```

Lemonade

How to use mach-kernel/ecu-pilot-q4km with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mach-kernel/ecu-pilot-q4km:Q4_K_M

Run and chat with the model

lemonade run user.ecu-pilot-q4km-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use mach-kernel/ecu-pilot-q4km with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf mach-kernel/ecu-pilot-q4km: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 mach-kernel/ecu-pilot-q4km:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use mach-kernel/ecu-pilot-q4km with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf mach-kernel/ecu-pilot-q4km: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 "mach-kernel/ecu-pilot-q4km: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"

mach-kernel commited on Apr 6

Commit

d714575

verified ·

1 Parent(s): da6b468

Add processor_config.json from fp16 source

Browse files

Files changed (1) hide show

processor_config.json +63 -0

processor_config.json ADDED Viewed

	@@ -0,0 +1,63 @@

+{
+  "image_processor": {
+    "data_format": "channels_first",
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "do_resize": true,
+    "image_mean": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "image_processor_type": "Qwen2VLImageProcessor",
+    "image_std": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "merge_size": 2,
+    "patch_size": 16,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098,
+    "size": {
+      "longest_edge": 16777216,
+      "shortest_edge": 65536
+    },
+    "temporal_patch_size": 2
+  },
+  "processor_class": "Qwen3VLProcessor",
+  "video_processor": {
+    "data_format": "channels_first",
+    "default_to_square": true,
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "do_resize": true,
+    "do_sample_frames": true,
+    "fps": 2,
+    "image_mean": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "image_std": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "max_frames": 768,
+    "merge_size": 2,
+    "min_frames": 4,
+    "patch_size": 16,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098,
+    "return_metadata": false,
+    "size": {
+      "longest_edge": 234881024,
+      "shortest_edge": 65536
+    },
+    "temporal_patch_size": 2,
+    "video_processor_type": "Qwen3VLVideoProcessor"
+  }
+}