Instructions to use evyatarXR/Yad2Photo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use evyatarXR/Yad2Photo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("undefined", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("evyatarXR/Yad2Photo") prompt = "Yad2 photo" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("undefined", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("evyatarXR/Yad2Photo")
prompt = "Yad2 photo"
image = pipe(prompt).images[0]Yad2Photo
Model description
Trigger words
You should use Yad2 photo 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/turbo-flux-trainer.
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