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
File size: 3,566 Bytes
f1e06e5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 | import io
from comfy_api.input_impl.video_types import (
container_to_output_format,
get_open_write_kwargs,
)
from comfy_api.util import VideoContainer
def test_container_to_output_format_empty_string():
"""Test that an empty string input returns None. `None` arg allows default auto-detection."""
assert container_to_output_format("") is None
def test_container_to_output_format_none():
"""Test that None input returns None."""
assert container_to_output_format(None) is None
def test_container_to_output_format_comma_separated():
"""Test that a comma-separated list returns a valid singular format from the list."""
comma_separated_format = "mp4,mov,m4a"
output_format = container_to_output_format(comma_separated_format)
assert output_format in comma_separated_format
def test_container_to_output_format_single():
"""Test that a single format string (not comma-separated list) is returned as is."""
assert container_to_output_format("mp4") == "mp4"
def test_get_open_write_kwargs_filepath_no_format():
"""Test that 'format' kwarg is NOT set when dest is a file path."""
kwargs_auto = get_open_write_kwargs("output.mp4", "mp4", VideoContainer.AUTO)
assert "format" not in kwargs_auto, "Format should not be set for file paths (AUTO)"
kwargs_specific = get_open_write_kwargs("output.avi", "mp4", "avi")
fail_msg = "Format should not be set for file paths (Specific)"
assert "format" not in kwargs_specific, fail_msg
def test_get_open_write_kwargs_base_options_mode():
"""Test basic kwargs for file path: mode and movflags."""
kwargs = get_open_write_kwargs("output.mp4", "mp4", VideoContainer.AUTO)
assert kwargs["mode"] == "w", "mode should be set to write"
fail_msg = "movflags should be set to preserve custom metadata tags"
assert "movflags" in kwargs["options"], fail_msg
assert kwargs["options"]["movflags"] == "use_metadata_tags", fail_msg
def test_get_open_write_kwargs_bytesio_auto_format():
"""Test kwargs for BytesIO dest with AUTO format."""
dest = io.BytesIO()
container_fmt = "mov,mp4,m4a"
kwargs = get_open_write_kwargs(dest, container_fmt, VideoContainer.AUTO)
assert kwargs["mode"] == "w"
assert kwargs["options"]["movflags"] == "use_metadata_tags"
fail_msg = (
"Format should be a valid format from the container's format list when AUTO"
)
assert kwargs["format"] in container_fmt, fail_msg
def test_get_open_write_kwargs_bytesio_specific_format():
"""Test kwargs for BytesIO dest with a specific single format."""
dest = io.BytesIO()
container_fmt = "avi"
to_fmt = VideoContainer.MP4
kwargs = get_open_write_kwargs(dest, container_fmt, to_fmt)
assert kwargs["mode"] == "w"
assert kwargs["options"]["movflags"] == "use_metadata_tags"
fail_msg = "Format should be the specified format (lowercased) when output format is not AUTO"
assert kwargs["format"] == "mp4", fail_msg
def test_get_open_write_kwargs_bytesio_specific_format_list():
"""Test kwargs for BytesIO dest with a specific comma-separated format."""
dest = io.BytesIO()
container_fmt = "avi"
to_fmt = "mov,mp4,m4a" # A format string that is a list
kwargs = get_open_write_kwargs(dest, container_fmt, to_fmt)
assert kwargs["mode"] == "w"
assert kwargs["options"]["movflags"] == "use_metadata_tags"
fail_msg = "Format should be a valid format from the specified format list when output format is not AUTO"
assert kwargs["format"] in to_fmt, fail_msg
|