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 / custom_nodes /ComfyUI-Manager /js /workflow-metadata.js

saik0s

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	/**
	* Attaches metadata to the workflow on save
	* - custom node pack version to all custom nodes used in the workflow
	*
	* Example metadata:
	* "nodes": {
	* "1": {
	* type: "CheckpointLoaderSimple",
	* ...
	* properties: {
	* cnr_id: "comfy-core",
	* version: "0.3.8",
	* },
	* },
	* }
	*
	* @typedef {Object} NodeInfo
	* @property {string} ver - Version (git hash or semantic version)
	* @property {string} cnr_id - ComfyRegistry node ID
	* @property {boolean} enabled - Whether the node is enabled
	*/

	import { app } from "../../scripts/app.js";
	import { api } from "../../scripts/api.js";

	class WorkflowMetadataExtension {
	constructor() {
	this.name = "Comfy.CustomNodesManager.WorkflowMetadata";
	this.installedNodes = {};
	this.comfyCoreVersion = null;
	}

	/**
	* Get the installed nodes info
	* @returns {Promise<Record<string, NodeInfo>>} The mapping from node name to its info.
	* ver can either be a git commit hash or a semantic version such as "1.0.0"
	* cnr_id is the id of the node in the ComfyRegistry
	* enabled is true if the node is enabled, false if it is disabled
	*/
	async getInstalledNodes() {
	const res = await api.fetchApi("/customnode/installed");
	return await res.json();
	}

	async init() {
	this.installedNodes = await this.getInstalledNodes();
	this.comfyCoreVersion = (await api.getSystemStats()).system.comfyui_version;
	}

	/**
	* Called when any node is created
	* @param {LGraphNode} node The newly created node
	*/
	nodeCreated(node) {
	try {
	// nodeData doesn't exist if node is missing or node is frontend only node
	if (!node?.constructor?.nodeData?.python_module) return;

	const nodeProperties = (node.properties ??= {});
	const modules = node.constructor.nodeData.python_module.split(".");
	const moduleType = modules[0];

	if (moduleType === "custom_nodes") {
	const nodePackageName = modules[1];
	const { cnr_id, aux_id, ver } =
	this.installedNodes[nodePackageName] ??
	this.installedNodes[nodePackageName.toLowerCase()] ??
	{};

	if (cnr_id === "comfy-core") return; // don't allow hijacking comfy-core name
	if (cnr_id) nodeProperties.cnr_id = cnr_id;
	else nodeProperties.aux_id = aux_id;
	if (ver) nodeProperties.ver = ver.trim();
	} else if (["nodes", "comfy_extras", "comfy_api_nodes"].includes(moduleType)) {
	nodeProperties.cnr_id = "comfy-core";
	nodeProperties.ver = this.comfyCoreVersion;
	}
	} catch (e) {
	console.error(e);
	}
	}
	}

	app.registerExtension(new WorkflowMetadataExtension());