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
- 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 typing import Any, Callable, Mapping | |
| DEFAULT_BOOL = ("BOOLEAN", {"default": False}) | |
| BOOL_UNARY_OPERATIONS: Mapping[str, Callable[[bool], bool]] = { | |
| "Not": lambda a: not a, | |
| } | |
| BOOL_BINARY_OPERATIONS: Mapping[str, Callable[[bool, bool], bool]] = { | |
| "Nor": lambda a, b: not (a or b), | |
| "Xor": lambda a, b: a ^ b, | |
| "Nand": lambda a, b: not (a and b), | |
| "And": lambda a, b: a and b, | |
| "Xnor": lambda a, b: not (a ^ b), | |
| "Or": lambda a, b: a or b, | |
| "Eq": lambda a, b: a == b, | |
| "Neq": lambda a, b: a != b, | |
| } | |
| class BoolUnaryOperation: | |
| def INPUT_TYPES(cls) -> Mapping[str, Any]: | |
| return { | |
| "required": {"op": (list(BOOL_UNARY_OPERATIONS.keys()),), "a": DEFAULT_BOOL} | |
| } | |
| RETURN_TYPES = ("BOOLEAN",) | |
| FUNCTION = "op" | |
| CATEGORY = "math/bool" | |
| def op(self, op: str, a: bool) -> tuple[bool]: | |
| return (BOOL_UNARY_OPERATIONS[op](a),) | |
| class BoolBinaryOperation: | |
| def INPUT_TYPES(cls) -> Mapping[str, Any]: | |
| return { | |
| "required": { | |
| "op": (list(BOOL_BINARY_OPERATIONS.keys()),), | |
| "a": DEFAULT_BOOL, | |
| "b": DEFAULT_BOOL, | |
| } | |
| } | |
| RETURN_TYPES = ("BOOLEAN",) | |
| FUNCTION = "op" | |
| CATEGORY = "math/bool" | |
| def op(self, op: str, a: bool, b: bool) -> tuple[bool]: | |
| return (BOOL_BINARY_OPERATIONS[op](a, b),) | |
| NODE_CLASS_MAPPINGS = { | |
| "CM_BoolUnaryOperation": BoolUnaryOperation, | |
| "CM_BoolBinaryOperation": BoolBinaryOperation, | |
| } | |