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
| import dayjs from 'dayjs' | |
| export const bytesToSize = ( | |
| bytes: number | string | undefined | null, | |
| decimals = 2, | |
| ) => { | |
| if (typeof bytes === 'undefined' || bytes === null) { | |
| bytes = 0 | |
| } | |
| if (typeof bytes === 'string') { | |
| bytes = Number(bytes) | |
| } | |
| if (Number.isNaN(bytes)) { | |
| return 'Unknown' | |
| } | |
| if (bytes === 0) { | |
| return '0 Bytes' | |
| } | |
| const k = 1024 | |
| const dm = decimals < 0 ? 0 : decimals | |
| const sizes = ['Bytes', 'KB', 'MB', 'GB', 'TB', 'PB', 'EB', 'ZB', 'YB'] | |
| const i = Math.floor(Math.log(bytes) / Math.log(k)) | |
| return parseFloat((bytes / Math.pow(k, i)).toFixed(dm)) + ' ' + sizes[i] | |
| } | |
| export const formatDate = (date: number | string | Date) => { | |
| return dayjs(date).format('YYYY-MM-DD HH:mm:ss') | |
| } | |
| export const previewUrlToFile = async (url: string) => { | |
| return fetch(url) | |
| .then((res) => res.blob()) | |
| .then((blob) => { | |
| const type = blob.type | |
| const extension = type.split('/')[1] | |
| const file = new File([blob], `preview.${extension}`, { type }) | |
| return file | |
| }) | |
| } | |
| // Model file extensions that are supported for direct download | |
| export const MODEL_FILE_EXTENSIONS = [ | |
| '.safetensors', | |
| '.ckpt', | |
| '.pt', | |
| '.pth', | |
| '.bin', | |
| '.onnx', | |
| '.tflite', | |
| '.pb', | |
| '.h5', | |
| '.pkl', | |
| '.pickle', | |
| '.json', // for configuration files | |
| '.yaml', | |
| '.yml', | |
| ] | |
| /** | |
| * Checks if a URL points directly to a downloadable model file | |
| */ | |
| export const isDirectFileUrl = (url: string): boolean => { | |
| if (!url || typeof url !== 'string') { | |
| return false | |
| } | |
| try { | |
| const urlObj = new URL(url) | |
| const pathname = urlObj.pathname.toLowerCase() | |
| // Check if the URL ends with a model file extension | |
| return MODEL_FILE_EXTENSIONS.some((ext) => pathname.endsWith(ext)) | |
| } catch { | |
| return false | |
| } | |
| } | |
| /** | |
| * Extracts filename from a URL | |
| */ | |
| export const getFilenameFromUrl = (url: string): string => { | |
| if (!url || typeof url !== 'string') { | |
| return 'model.bin' | |
| } | |
| try { | |
| const urlObj = new URL(url) | |
| const pathname = urlObj.pathname | |
| const filename = pathname.split('/').pop() || '' | |
| // If no filename with extension found, generate one | |
| if (!filename || !filename.includes('.')) { | |
| const extension = | |
| MODEL_FILE_EXTENSIONS.find((ext) => | |
| pathname.toLowerCase().endsWith(ext), | |
| ) || '.bin' | |
| return `model${extension}` | |
| } | |
| return filename | |
| } catch { | |
| return 'model.bin' | |
| } | |
| } | |
| /** | |
| * Determines model type based on file extension (fallback only) | |
| * Note: This is now primarily used as a fallback when no manual selection is made | |
| */ | |
| export const getModelTypeFromFilename = (filename: string): string => { | |
| if (!filename || typeof filename !== 'string') { | |
| return 'checkpoints' | |
| } | |
| const extension = filename.toLowerCase().split('.').pop() | |
| switch (extension) { | |
| case 'safetensors': | |
| case 'ckpt': | |
| case 'pt': | |
| case 'pth': | |
| return 'checkpoints' // Default for these extensions, but user can override | |
| case 'bin': | |
| return 'diffusers' | |
| case 'onnx': | |
| return 'onnx' | |
| case 'tflite': | |
| return 'tflite' | |
| case 'pb': | |
| return 'tensorflow' | |
| case 'h5': | |
| return 'keras' | |
| case 'pkl': | |
| case 'pickle': | |
| return 'embeddings' | |
| default: | |
| return 'checkpoints' | |
| } | |
| } | |