Instructions to use prithivMLmods/Past-Present-Deep-Mix-Flux-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use prithivMLmods/Past-Present-Deep-Mix-Flux-LoRA 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("prithivMLmods/Past-Present-Deep-Mix-Flux-LoRA") prompt = "Mixing Past and Present, a human hand is holding a small, square, black-and-white photograph of a cityscape. The photograph is taken from a low angle, looking up at the viewer. The hand is positioned in front of a gray road with white lines painted on it. To the left of the photograph is a black metal fence, and to the right of the fence is a tall brick building with balconies and balconies. The building is a light brown color, and there are cars parked on the street. The sky is blue, dotted with white clouds, adding a pop of color to the scene." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 49bffa0f1a92dfd296746fd18eb6b3933aef3ec9a498da6f1c4e2e85ed9f3807
- Size of remote file:
- 133 kB
- SHA256:
- f3e52651bbd807a07d4488fd95beaedada1b80aeedb80f658f1334fd02b47a6c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.