Instructions to use saik0s/comfy_backup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use saik0s/comfy_backup with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="saik0s/comfy_backup",
	filename="ComfyUI/models/text_encoders/gemma-3-12b-it-q2_k.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use saik0s/comfy_backup 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 saik0s/comfy_backup:Q4_K_S
# Run inference directly in the terminal:
llama cli -hf saik0s/comfy_backup:Q4_K_S

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf saik0s/comfy_backup:Q4_K_S
# Run inference directly in the terminal:
llama cli -hf saik0s/comfy_backup:Q4_K_S

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 saik0s/comfy_backup:Q4_K_S
# Run inference directly in the terminal:
./llama-cli -hf saik0s/comfy_backup:Q4_K_S

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 saik0s/comfy_backup:Q4_K_S
# Run inference directly in the terminal:
./build/bin/llama-cli -hf saik0s/comfy_backup:Q4_K_S

Use Docker

docker model run hf.co/saik0s/comfy_backup:Q4_K_S

LM Studio
Jan
Ollama
How to use saik0s/comfy_backup with Ollama:
```
ollama run hf.co/saik0s/comfy_backup:Q4_K_S
```

Unsloth Studio

How to use saik0s/comfy_backup 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 saik0s/comfy_backup 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 saik0s/comfy_backup to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for saik0s/comfy_backup to start chatting

How to use saik0s/comfy_backup with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf saik0s/comfy_backup:Q4_K_S

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": "saik0s/comfy_backup:Q4_K_S"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use saik0s/comfy_backup with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf saik0s/comfy_backup:Q4_K_S

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 saik0s/comfy_backup:Q4_K_S

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use saik0s/comfy_backup with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf saik0s/comfy_backup:Q4_K_S

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 "saik0s/comfy_backup:Q4_K_S" \
  --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"

Docker Model Runner
How to use saik0s/comfy_backup with Docker Model Runner:
```
docker model run hf.co/saik0s/comfy_backup:Q4_K_S
```

Lemonade

How to use saik0s/comfy_backup with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull saik0s/comfy_backup:Q4_K_S

Run and chat with the model

lemonade run user.comfy_backup-Q4_K_S

List all available models

lemonade list

comfy_backup / ComfyUI /user /default /comfy.settings.json

saik0s

Upload ComfyUI/user/default/comfy.settings.json with huggingface_hub

6974a03 verified 1 day ago

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	{
	"Comfy.CustomColorPalettes": {
	"obsidian": {
	"version": 112,
	"id": "obsidian",
	"name": "Obsidian",
	"colors": {
	"node_slot": {
	"CLIP": "#FFD500",
	"CLIP_VISION": "#A8DADC",
	"CLIP_VISION_OUTPUT": "#ad7452",
	"CONDITIONING": "#FFA931",
	"CONTROL_NET": "#6EE7B7",
	"IMAGE": "#64B5F6",
	"LATENT": "#FF9CF9",
	"MASK": "#81C784",
	"MODEL": "#B39DDB",
	"STYLE_MODEL": "#C2FFAE",
	"VAE": "#FF6E6E",
	"TAESD": "#DCC274",
	"PIPE_LINE": "#7737AA",
	"PIPE_LINE_SDXL": "#7737AA",
	"INT": "#29699C",
	"X_Y": "#38291f",
	"XYPLOT": "#74DA5D",
	"LORA_STACK": "#94dccd",
	"CONTROL_NET_STACK": "#94dccd",
	"FAST_MODEL_LOADER": "#ffd399",
	"SAMPLING": "#60a5fa"
	},
	"litegraph_base": {
	"BACKGROUND_IMAGE": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAGQAAABkCAIAAAD/gAIDAAAAGXRFWHRTb2Z0d2FyZQBBZG9iZSBJbWFnZVJlYWR5ccllPAAAAQBJREFUeNrs1rEKwjAUhlETUkj3vP9rdmr1Ysammk2w5wdxuLgcMHyptfawuZX4pJSWZTnfnu/lnIe/jNNxHHGNn//HNbbv+4dr6V+11uF527arU7+u63qfa/bnmh8sWLBgwYJlqRf8MEptXPBXJXa37BSl3ixYsGDBMliwFLyCV/DeLIMFCxYsWLBMwSt4Be/NggXLYMGCBUvBK3iNruC9WbBgwYJlsGApeAWv4L1ZBgsWLFiwYJmCV/AK3psFC5bBggULloJX8BpdwXuzYMGCBctgwVLwCl7Be7MMFixYsGDBsu8FH1FaSmExVfAxBa/gvVmwYMGCZbBg/W4vAQYA5tRF9QYlv/QAAAAASUVORK5CYII=",
	"CLEAR_BACKGROUND_COLOR": "#222222",
	"NODE_TITLE_COLOR": "#d4d4d8",
	"NODE_SELECTED_TITLE_COLOR": "#ffffff",
	"NODE_TEXT_SIZE": 14,
	"NODE_TEXT_COLOR": "#ffffff",
	"NODE_SUBTEXT_SIZE": 12,
	"NODE_DEFAULT_COLOR": "#09090b",
	"NODE_DEFAULT_BGCOLOR": "rgba(24,24,27,.9)",
	"NODE_DEFAULT_BOXCOLOR": "rgba(255,255,255,.75)",
	"NODE_DEFAULT_SHAPE": 2,
	"NODE_BOX_OUTLINE_COLOR": "#60a5fa",
	"NODE_BYPASS_BGCOLOR": "#FF00FF",
	"NODE_ERROR_COLOUR": "#E00",
	"DEFAULT_SHADOW_COLOR": "rgba(0,0,0,0)",
	"DEFAULT_GROUP_FONT": 24,
	"WIDGET_BGCOLOR": "#242427",
	"WIDGET_OUTLINE_COLOR": "#3f3f46",
	"WIDGET_TEXT_COLOR": "#d4d4d8",
	"WIDGET_SECONDARY_TEXT_COLOR": "#d4d4d8",
	"LINK_COLOR": "#9A9",
	"EVENT_LINK_COLOR": "#A86",
	"CONNECTING_LINK_COLOR": "#AFA"
	},
	"comfy_base": {
	"fg-color": "#fff",
	"bg-color": "#09090b",
	"comfy-menu-bg": "rgba(24,24,24,.9)",
	"comfy-input-bg": "#262626",
	"input-text": "#ddd",
	"descrip-text": "#999",
	"drag-text": "#ccc",
	"error-text": "#ff4444",
	"border-color": "#29292c",
	"tr-even-bg-color": "rgba(28,28,28,.9)",
	"tr-odd-bg-color": "rgba(19,19,19,.9)"
	}
	}
	},
	"obsidian_dark": {
	"version": 112,
	"id": "obsidian_dark",
	"name": "Obsidian Dark",
	"colors": {
	"node_slot": {
	"CLIP": "#FFD500",
	"CLIP_VISION": "#A8DADC",
	"CLIP_VISION_OUTPUT": "#ad7452",
	"CONDITIONING": "#FFA931",
	"CONTROL_NET": "#6EE7B7",
	"IMAGE": "#64B5F6",
	"LATENT": "#FF9CF9",
	"MASK": "#81C784",
	"MODEL": "#B39DDB",
	"STYLE_MODEL": "#C2FFAE",
	"VAE": "#FF6E6E",
	"TAESD": "#DCC274",
	"PIPE_LINE": "#7737AA",
	"PIPE_LINE_SDXL": "#7737AA",
	"INT": "#29699C",
	"X_Y": "#38291f",
	"XYPLOT": "#74DA5D",
	"LORA_STACK": "#94dccd",
	"CONTROL_NET_STACK": "#94dccd",
	"FAST_MODEL_LOADER": "#ffd399",
	"SAMPLING": "#60a5fa"
	},
	"litegraph_base": {
	"BACKGROUND_IMAGE": "data:image/png;base64,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",
	"CLEAR_BACKGROUND_COLOR": "#09090b",
	"NODE_TITLE_COLOR": "#d4d4d8",
	"NODE_SELECTED_TITLE_COLOR": "#ffffff",
	"NODE_TEXT_SIZE": 14,
	"NODE_TEXT_COLOR": "#ffffff",
	"NODE_SUBTEXT_SIZE": 12,
	"NODE_DEFAULT_COLOR": "#09090b",
	"NODE_DEFAULT_BGCOLOR": "rgba(24,24,27,.9)",
	"NODE_DEFAULT_BOXCOLOR": "rgba(255,255,255,.75)",
	"NODE_DEFAULT_SHAPE": 2,
	"NODE_BOX_OUTLINE_COLOR": "#60a5fa",
	"NODE_BYPASS_BGCOLOR": "#FF00FF",
	"NODE_ERROR_COLOUR": "#E00",
	"DEFAULT_SHADOW_COLOR": "rgba(0,0,0,0)",
	"DEFAULT_GROUP_FONT": 24,
	"WIDGET_BGCOLOR": "#242427",
	"WIDGET_OUTLINE_COLOR": "#3f3f46",
	"WIDGET_TEXT_COLOR": "#d4d4d8",
	"WIDGET_SECONDARY_TEXT_COLOR": "#d4d4d8",
	"LINK_COLOR": "#9A9",
	"EVENT_LINK_COLOR": "#A86",
	"CONNECTING_LINK_COLOR": "#AFA"
	},
	"comfy_base": {
	"fg-color": "#fff",
	"bg-color": "#09090b",
	"comfy-menu-bg": "rgba(24,24,24,.9)",
	"comfy-input-bg": "#262626",
	"input-text": "#ddd",
	"descrip-text": "#999",
	"drag-text": "#ccc",
	"error-text": "#ff4444",
	"border-color": "#29292c",
	"tr-even-bg-color": "rgba(28,28,28,.9)",
	"tr-odd-bg-color": "rgba(19,19,19,.9)"
	}
	}
	}
	},
	"ModelManager.APIKey.Civitai": null,
	"ModelManager.APIKey.HuggingFace": null,
	"Comfy.Canvas.LeftMouseClickBehavior": "select",
	"Comfy.Canvas.MouseWheelScroll": "panning",
	"Comfy.Canvas.NavigationMode": "custom",
	"downloaderbackup.file_size_limit": 50,
	"downloaderbackup.repo_name": "https://huggingface.co/saik0s/comfy_backup",
	"downloader.auto_open_missing_models_on_run": false
	}