Instructions to use aka7774/comfyui-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aka7774/comfyui-models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("aka7774/comfyui-models", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - llama-cpp-python
How to use aka7774/comfyui-models with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="aka7774/comfyui-models", filename="SEEDVR2/seedvr2_ema_7b-Q4_K_M.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use aka7774/comfyui-models 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 aka7774/comfyui-models:UD-Q4_K_XL # Run inference directly in the terminal: llama cli -hf aka7774/comfyui-models:UD-Q4_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf aka7774/comfyui-models:UD-Q4_K_XL # Run inference directly in the terminal: llama cli -hf aka7774/comfyui-models:UD-Q4_K_XL
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 aka7774/comfyui-models:UD-Q4_K_XL # Run inference directly in the terminal: ./llama-cli -hf aka7774/comfyui-models:UD-Q4_K_XL
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 aka7774/comfyui-models:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama-cli -hf aka7774/comfyui-models:UD-Q4_K_XL
Use Docker
docker model run hf.co/aka7774/comfyui-models:UD-Q4_K_XL
- LM Studio
- Jan
- Ollama
How to use aka7774/comfyui-models with Ollama:
ollama run hf.co/aka7774/comfyui-models:UD-Q4_K_XL
- Unsloth Studio
How to use aka7774/comfyui-models 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 aka7774/comfyui-models 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 aka7774/comfyui-models to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for aka7774/comfyui-models to start chatting
- Atomic Chat new
- Docker Model Runner
How to use aka7774/comfyui-models with Docker Model Runner:
docker model run hf.co/aka7774/comfyui-models:UD-Q4_K_XL
- Lemonade
How to use aka7774/comfyui-models with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull aka7774/comfyui-models:UD-Q4_K_XL
Run and chat with the model
lemonade run user.comfyui-models-UD-Q4_K_XL
List all available models
lemonade list
ComfyUI clean public model recovery repository
This repository contains only artifacts classified as public in the pinned recovery manifest. It does not apply one blanket license: each artifact retains its upstream license and usage conditions.
- Manifest category:
public - Logical model paths:
295 - Regular-file bytes:
844592536015 - Source of truth:
recovery/model-manifest.jsonl - Symbolic links:
recovery/symlink-aliases.json
Restore paths are relative to ComfyUI/models/. Verify SHA-256 before use.
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Hardware compatibility
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