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
| from __future__ import annotations | |
| from typing import TypedDict | |
| import os | |
| import folder_paths | |
| import glob | |
| from aiohttp import web | |
| import hashlib | |
| class Source: | |
| custom_node = "custom_node" | |
| templates = "templates" | |
| class SubgraphEntry(TypedDict): | |
| source: str | |
| """ | |
| Source of subgraph - custom_nodes vs templates. | |
| """ | |
| path: str | |
| """ | |
| Relative path of the subgraph file. | |
| For custom nodes, will be the relative directory like <custom_node_dir>/subgraphs/<name>.json | |
| """ | |
| name: str | |
| """ | |
| Name of subgraph file. | |
| """ | |
| info: CustomNodeSubgraphEntryInfo | |
| """ | |
| Additional info about subgraph; in the case of custom_nodes, will contain nodepack name | |
| """ | |
| data: str | |
| class CustomNodeSubgraphEntryInfo(TypedDict): | |
| node_pack: str | |
| """Node pack name.""" | |
| class SubgraphManager: | |
| def __init__(self): | |
| self.cached_custom_node_subgraphs: dict[SubgraphEntry] | None = None | |
| self.cached_blueprint_subgraphs: dict[SubgraphEntry] | None = None | |
| def _create_entry(self, file: str, source: str, node_pack: str) -> tuple[str, SubgraphEntry]: | |
| """Create a subgraph entry from a file path. Expects normalized path (forward slashes).""" | |
| entry_id = hashlib.sha256(f"{source}{file}".encode()).hexdigest() | |
| entry: SubgraphEntry = { | |
| "source": source, | |
| "name": os.path.splitext(os.path.basename(file))[0], | |
| "path": file, | |
| "info": {"node_pack": node_pack}, | |
| } | |
| return entry_id, entry | |
| async def load_entry_data(self, entry: SubgraphEntry): | |
| with open(entry['path'], 'r', encoding='utf-8') as f: | |
| entry['data'] = f.read() | |
| return entry | |
| async def sanitize_entry(self, entry: SubgraphEntry | None, remove_data=False) -> SubgraphEntry | None: | |
| if entry is None: | |
| return None | |
| entry = entry.copy() | |
| entry.pop('path', None) | |
| if remove_data: | |
| entry.pop('data', None) | |
| return entry | |
| async def sanitize_entries(self, entries: dict[str, SubgraphEntry], remove_data=False) -> dict[str, SubgraphEntry]: | |
| entries = entries.copy() | |
| for key in list(entries.keys()): | |
| entries[key] = await self.sanitize_entry(entries[key], remove_data) | |
| return entries | |
| async def get_custom_node_subgraphs(self, loadedModules, force_reload=False): | |
| """Load subgraphs from custom nodes.""" | |
| if not force_reload and self.cached_custom_node_subgraphs is not None: | |
| return self.cached_custom_node_subgraphs | |
| subgraphs_dict: dict[SubgraphEntry] = {} | |
| for folder in folder_paths.get_folder_paths("custom_nodes"): | |
| pattern = os.path.join(folder, "*/subgraphs/*.json") | |
| for file in glob.glob(pattern): | |
| file = file.replace('\\', '/') | |
| node_pack = "custom_nodes." + file.split('/')[-3] | |
| entry_id, entry = self._create_entry(file, Source.custom_node, node_pack) | |
| subgraphs_dict[entry_id] = entry | |
| self.cached_custom_node_subgraphs = subgraphs_dict | |
| return subgraphs_dict | |
| async def get_blueprint_subgraphs(self, force_reload=False): | |
| """Load subgraphs from the blueprints directory.""" | |
| if not force_reload and self.cached_blueprint_subgraphs is not None: | |
| return self.cached_blueprint_subgraphs | |
| subgraphs_dict: dict[SubgraphEntry] = {} | |
| blueprints_dir = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'blueprints') | |
| if os.path.exists(blueprints_dir): | |
| for file in glob.glob(os.path.join(blueprints_dir, "*.json")): | |
| file = file.replace('\\', '/') | |
| entry_id, entry = self._create_entry(file, Source.templates, "comfyui") | |
| subgraphs_dict[entry_id] = entry | |
| self.cached_blueprint_subgraphs = subgraphs_dict | |
| return subgraphs_dict | |
| async def get_all_subgraphs(self, loadedModules, force_reload=False): | |
| """Get all subgraphs from all sources (custom nodes and blueprints).""" | |
| custom_node_subgraphs = await self.get_custom_node_subgraphs(loadedModules, force_reload) | |
| blueprint_subgraphs = await self.get_blueprint_subgraphs(force_reload) | |
| return {**custom_node_subgraphs, **blueprint_subgraphs} | |
| async def get_subgraph(self, id: str, loadedModules): | |
| """Get a specific subgraph by ID from any source.""" | |
| entry = (await self.get_all_subgraphs(loadedModules)).get(id) | |
| if entry is not None and entry.get('data') is None: | |
| await self.load_entry_data(entry) | |
| return entry | |
| def add_routes(self, routes, loadedModules): | |
| async def get_global_subgraphs(request): | |
| subgraphs_dict = await self.get_all_subgraphs(loadedModules) | |
| return web.json_response(await self.sanitize_entries(subgraphs_dict, remove_data=True)) | |
| async def get_global_subgraph(request): | |
| id = request.match_info.get("id", None) | |
| subgraph = await self.get_subgraph(id, loadedModules) | |
| return web.json_response(await self.sanitize_entry(subgraph)) | |