Instructions to use dn6/flux2-modular-bnb-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dn6/flux2-modular-bnb-4bit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dn6/flux2-modular-bnb-4bit", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
This is a modular diffusion pipeline built with 🧨 Diffusers' modular pipeline framework.
Pipeline Type: SequentialPipelineBlocks
Description:
This pipeline uses a 0-block architecture that can be customized and extended.
Example Usage
[TODO]
Pipeline Architecture
This modular pipeline is composed of the following blocks:
No blocks defined.
Model Components
No specific components required. Components can be loaded dynamically.
Input/Output Specification
Inputs No specific inputs defined.
Outputs Standard pipeline outputs.
- Downloads last month
- -