Instructions to use saik0s/comfy_backup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
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
- Pi
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
| /** | |
| * Dynamic image inputs for OpenRouter Node | |
| * Based on cozy_ex_dynamic pattern for clean dynamic inputs | |
| */ | |
| import { app } from "../../../scripts/app.js" | |
| const TypeSlot = { | |
| Input: 1, | |
| Output: 2, | |
| }; | |
| const TypeSlotEvent = { | |
| Connect: true, | |
| Disconnect: false, | |
| }; | |
| const NODE_ID = "OpenRouterNode"; | |
| const PREFIX = "image"; | |
| const TYPE = "IMAGE"; | |
| app.registerExtension({ | |
| name: 'OpenRouter.DynamicImageInputs', | |
| async beforeRegisterNodeDef(nodeType, nodeData, app) { | |
| // Skip if not our node | |
| if (nodeData.name !== NODE_ID) { | |
| return | |
| } | |
| const onNodeCreated = nodeType.prototype.onNodeCreated; | |
| nodeType.prototype.onNodeCreated = function () { | |
| const me = onNodeCreated?.apply(this); | |
| // Find api_key widget and update label with security warning | |
| const apiKeyWidget = this.widgets?.find(w => w.name === "api_key"); | |
| if (apiKeyWidget) { | |
| apiKeyWidget.label = "api_key (Leave blank for secure loading)"; | |
| } | |
| // Start with a new dynamic input - exactly like cozy example | |
| this.addInput(PREFIX, TYPE); | |
| // Ensure the new slot has proper appearance | |
| const slot = this.inputs[this.inputs.length - 1]; | |
| if (slot) { | |
| slot.color_off = "#666"; | |
| } | |
| return me; | |
| } | |
| const onConnectionsChange = nodeType.prototype.onConnectionsChange | |
| nodeType.prototype.onConnectionsChange = function (slotType, slot_idx, event, link_info, node_slot) { | |
| const me = onConnectionsChange?.apply(this, arguments); | |
| if (slotType === TypeSlot.Input) { | |
| // Only process image inputs | |
| if (node_slot && !node_slot.name.startsWith(PREFIX)) { | |
| return me; | |
| } | |
| if (link_info && event === TypeSlotEvent.Connect) { | |
| // Get the parent (left side node) from the link | |
| const fromNode = this.graph._nodes.find( | |
| (otherNode) => otherNode.id == link_info.origin_id | |
| ) | |
| if (fromNode) { | |
| // Make sure there is a parent for the link | |
| const parent_link = fromNode.outputs[link_info.origin_slot]; | |
| if (parent_link) { | |
| node_slot.type = parent_link.type; | |
| node_slot.name = `${PREFIX}_`; | |
| } | |
| } | |
| } else if (event === TypeSlotEvent.Disconnect) { | |
| // Don't remove the slot immediately, let the cleanup below handle it | |
| } | |
| // Track each slot name so we can index the uniques | |
| let idx = 0; | |
| let slot_tracker = {}; | |
| let toRemove = []; | |
| for(const slot of this.inputs) { | |
| // Skip non-image inputs | |
| if (!slot.name.startsWith(PREFIX)) { | |
| idx += 1; | |
| continue; | |
| } | |
| // Mark empty image slots for removal (except the last one) | |
| if (slot.link === null && idx < this.inputs.length - 1) { | |
| toRemove.push(idx); | |
| } else if (slot.link !== null) { | |
| // Connected slot - update its name with proper index | |
| const name = slot.name.split('_')[0]; | |
| let count = (slot_tracker[name] || 0) + 1; | |
| slot_tracker[name] = count; | |
| slot.name = `${name}_${count}`; | |
| } | |
| idx += 1; | |
| } | |
| // Remove empty slots from highest index to lowest | |
| toRemove.reverse(); | |
| for(const removeIdx of toRemove) { | |
| this.removeInput(removeIdx); | |
| } | |
| // Check if the last input is an image input | |
| let lastInput = null; | |
| for (let i = this.inputs.length - 1; i >= 0; i--) { | |
| if (this.inputs[i].name.startsWith(PREFIX)) { | |
| lastInput = this.inputs[i]; | |
| break; | |
| } | |
| } | |
| // If there's no empty image slot at the end, or no image slots at all, add one | |
| if (!lastInput || lastInput.link !== null) { | |
| this.addInput(PREFIX, TYPE); | |
| // Set the unconnected slot to appear gray | |
| const newSlot = this.inputs[this.inputs.length - 1]; | |
| if (newSlot) { | |
| newSlot.color_off = "#666"; | |
| } | |
| } | |
| // Force the node to resize itself for the new/deleted connections | |
| this?.graph?.setDirtyCanvas(true); | |
| return me; | |
| } | |
| } | |
| return nodeType; | |
| }, | |
| }) |