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-model-manager /src /components /ModelCard.vue

saik0s

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f1e06e5 verified 22 days ago

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	<template>
	<div
	ref="container"
	class="relative h-full select-none rounded-lg hover:bg-gray-500/40"
	>
	<div data-card-main class="flex h-full w-full flex-col">
	<div data-card-preview class="flex-1 overflow-hidden">
	<div v-if="model.isFolder" class="h-full w-full">
	<svg
	class="icon"
	viewBox="0 0 1024 1024"
	version="1.1"
	xmlns="http://www.w3.org/2000/svg"
	width="100%"
	height="100%"
	>
	<path
	d="M853.333333 256H469.333333l-85.333333-85.333333H170.666667c-46.933333 0-85.333333 38.4-85.333334 85.333333v170.666667h853.333334v-85.333334c0-46.933333-38.4-85.333333-85.333334-85.333333z"
	fill="#FFA000"
	></path>
	<path
	d="M853.333333 256H170.666667c-46.933333 0-85.333333 38.4-85.333334 85.333333v426.666667c0 46.933333 38.4 85.333333 85.333334 85.333333h682.666666c46.933333 0 85.333333-38.4 85.333334-85.333333V341.333333c0-46.933333-38.4-85.333333-85.333334-85.333333z"
	fill="#FFCA28"
	></path>
	</svg>
	</div>
	<div
	v-else-if="isVideoUrl(preview)"
	class="h-full w-full p-1 hover:p-0"
	>
	<PreviewVideo :src="preview" />
	</div>
	<div v-else class="h-full w-full p-1 hover:p-0">
	<img class="h-full w-full rounded-lg object-cover" :src="preview" />
	</div>
	</div>

	<slot name="name">
	<div class="flex justify-center overflow-hidden px-1">
	<span class="overflow-hidden text-ellipsis whitespace-nowrap">
	{{ model.basename }}
	</span>
	</div>
	</slot>
	</div>

	<div
	v-if="!model.isFolder"
	data-draggable-overlay
	class="absolute left-0 top-0 h-full w-full"
	draggable="true"
	@dragend.stop="dragToAddModelNode(model, $event)"
	></div>

	<div
	v-if="!model.isFolder"
	data-mode-type
	class="pointer-events-none absolute left-2 top-2"
	:style="{
	transform: `scale(${typeLabelScale})`,
	transformOrigin: 'left top',
	}"
	>
	<div class="rounded-full bg-black/50 px-3 py-1">
	<span>{{ model.type }}</span>
	</div>
	</div>

	<slot name="extra"></slot>
	</div>
	</template>

	<script setup lang="ts">
	import { useElementSize } from '@vueuse/core'
	import PreviewVideo from 'components/PreviewVideo.vue'
	import { useModelNodeAction } from 'hooks/model'
	import { BaseModel } from 'types/typings'
	import { isVideoUrl } from 'utils/media'
	import { computed, ref } from 'vue'

	interface Props {
	model: BaseModel
	}

	const props = defineProps<Props>()

	const preview = computed(() =>
	Array.isArray(props.model.preview)
	? props.model.preview[0]
	: props.model.preview,
	)

	const container = ref<HTMLElement \| null>(null)

	const { width } = useElementSize(container)

	const typeLabelScale = computed(() => {
	return width.value / 200
	})

	const { dragToAddModelNode } = useModelNodeAction()
	</script>