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 { useLoading } from 'hooks/loading' | |
| import { api } from 'scripts/comfyAPI' | |
| import { onMounted, ref } from 'vue' | |
| export const request = async (url: string, options?: RequestInit) => { | |
| return api | |
| .fetchApi(`/model-manager${url}`, options) | |
| .then((response) => response.json()) | |
| .then((resData) => { | |
| if (resData.success) { | |
| return resData.data | |
| } | |
| throw new Error(resData.error) | |
| }) | |
| } | |
| export interface RequestOptions<T> { | |
| method?: RequestInit['method'] | |
| headers?: RequestInit['headers'] | |
| defaultParams?: Record<string, any> | |
| defaultValue?: any | |
| postData?: (data: T) => T | |
| manual?: boolean | |
| } | |
| export const useRequest = <T = any>( | |
| url: string, | |
| options: RequestOptions<T> = {}, | |
| ) => { | |
| const loading = useLoading() | |
| const postData = options.postData ?? ((data) => data) | |
| const data = ref<T>(options.defaultValue) | |
| const lastParams = ref() | |
| const fetch = async ( | |
| params: Record<string, any> = options.defaultParams ?? {}, | |
| ) => { | |
| loading.show() | |
| lastParams.value = params | |
| let requestUrl = url | |
| const requestOptions: RequestInit = { | |
| method: options.method, | |
| headers: options.headers, | |
| } | |
| const requestParams = { ...params } | |
| const templatePattern = /\{(.*?)\}/g | |
| const urlParamKeyMatches = requestUrl.matchAll(templatePattern) | |
| for (const urlParamKey of urlParamKeyMatches) { | |
| const [match, paramKey] = urlParamKey | |
| if (paramKey in requestParams) { | |
| const paramValue = requestParams[paramKey] | |
| delete requestParams[paramKey] | |
| requestUrl = requestUrl.replace(match, paramValue) | |
| } | |
| } | |
| if (!requestOptions.method) { | |
| requestOptions.method = 'GET' | |
| } | |
| if (requestOptions.method !== 'GET') { | |
| requestOptions.body = JSON.stringify(requestParams) | |
| } | |
| return request(requestUrl, requestOptions) | |
| .then((resData) => (data.value = postData(resData))) | |
| .finally(() => loading.hide()) | |
| } | |
| onMounted(() => { | |
| if (!options.manual) { | |
| fetch() | |
| } | |
| }) | |
| const refresh = async () => { | |
| return fetch(lastParams.value) | |
| } | |
| return { data, refresh, fetch } | |
| } | |