Instructions to use alexShangeeth/dpr_inpaint_After with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alexShangeeth/dpr_inpaint_After 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("alexShangeeth/dpr_inpaint_After") prompt = "dpr20strip" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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("alexShangeeth/dpr_inpaint_After")
prompt = "dpr20strip"
image = pipe(prompt).images[0]dpr_inpaint_After
Model description
train 2000 steps with inpaint pics
Trigger words
You should use dpr20strip to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Training at fal.ai
Training was done using fal.ai/models/fal-ai/flux-lora-general-training.
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Model tree for alexShangeeth/dpr_inpaint_After
Base model
black-forest-labs/FLUX.1-dev