Instructions to use roktimsardar123/rosxy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use roktimsardar123/rosxy 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("roktimsardar123/rosxy") prompt = "A person in a bustling cafe ROSXY" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
rosxy
Model trained with AI Toolkit by Ostris

- Prompt
- A person in a bustling cafe ROSXY

- Prompt
- ROSXY, sleeping in bed

- Prompt
- ROSXY, RAW realistic portrait in mountain view
Trigger words
You should use ROSXY to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('roktimsardar123/rosxy', weight_name='rosxy.safetensors')
image = pipeline('A person in a bustling cafe ROSXY').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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Model tree for roktimsardar123/rosxy
Base model
black-forest-labs/FLUX.1-dev