Instructions to use Reza2kn/XRAY with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Reza2kn/XRAY 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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Reza2kn/XRAY") prompt = "chest XRAY image of 50 year old male with bilateral secondary PTB with right upper atelectasis, right pleural adhesions, left compensatory emphysema" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 689 Bytes
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tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: >-
chest XRAY image of 50 year old male with bilateral secondary PTB with
right upper atelectasis, right pleural adhesions, left compensatory
emphysema
output:
url: images/1728521628967__000016669_0.jpg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: XRAY
---
# XRAY
<Gallery />
## Model description
Tryin' somethin' here. v1
## Trigger words
You should use `XRAY` to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Download](/Reza2kn/XRAY/tree/main) them in the Files & versions tab.
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