Instructions to use ostris/Flex.2-preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ostris/Flex.2-preview with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ostris/Flex.2-preview", 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 Settings
- Draw Things
- DiffusionBee
dataset
#11
by raulc0399 - opened
Hi, thank you for you work.
do you have a sample of the dataset that you used?
also how did you train the conditioning and inpaint? can those be fine-tuned as well?
i think i found the answers to questions 2 and 3:
https://github.com/ostris/ai-toolkit/blob/2b4c525489c6fd42a8e99724d9c528b3dcbecb92/config/examples/train_lora_flex2_24gb.yaml#L39