Instructions to use 75AI/Checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 75AI/Checkpoint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("75AI/Checkpoint") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
File size: 660 Bytes
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tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/F5AI-75AI Dress Vouge (1).png
text: '-'
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: null
---
# Checkpoint Flux1 Synthetic Raw
<Gallery />
## Model description
Checkpoint Flux1 Realism is a versatile model built to handle a wide range of creative product types. It aims to combine flexibility, efficiency, and quick understanding into a unified model.
This model includes:
Photography content (80%)
Art and animation content (20%)
## Download model
[Download](/75AI/Checkpoint/tree/main) them in the Files & versions tab.
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