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("Himanshu806/statusofbudha")
prompt = "small Buddha statue on pedestal statusOfBudhaLoRA"
image = pipe(prompt).images[0]statusofbudha
Model trained with AI Toolkit by Ostris
- Prompt
- small Buddha statue on pedestal statusOfBudhaLoRA
- Prompt
- small Buddha statue on stone in mountains statusOfBudhaLoRA
Trigger words
You should use statusOfBudhaLoRA 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('Himanshu806/statusofbudha', weight_name='statusofbudha.safetensors')
image = pipeline('small Buddha statue on pedestal statusOfBudhaLoRA').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 Himanshu806/statusofbudha
Base model
black-forest-labs/FLUX.1-dev