Instructions to use Edweibin/stb-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Edweibin/stb-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("Edweibin/stb-lora") prompt = "a girl laughing" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
File size: 886 Bytes
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tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: a girl laughing
output:
url: images/image.webp
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: anything
license: cc-by-nc-4.0
---
# Pola Photo (Flux Dev)
<Gallery />
## Model description
This model creates realistic pictures reminiscent of popular instant photo styles, such as Polaroid.
This was trained thanks to Replicate, on their platform. It was trained with open source materials and falls under the same license as Flux Dev, with the addition of CC non commercial with attribution for any additional elements.
## Trigger words
You should use `polaroid style` to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Download](/Edweibin/flux-dev-nfsw/tree/main) them in the Files & versions tab. |