Instructions to use mlgawd/sydneypi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mlgawd/sydneypi 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("mlgawd/sydneypi") prompt = "hot sweeney at the beach" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
my_first_flux_lora_v2
Model trained with AI Toolkit by Ostris

- Prompt
- hot sweeney at the beach

- Prompt
- hot sweeney holding a coffee cup, in a beanie, sitting at a cafe
Trigger words
No trigger words defined.
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('mlgawd/sydneypi', weight_name='my_first_flux_lora_v2.safetensors')
image = pipeline('hot sweeney at the beach').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
- Downloads last month
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Model tree for mlgawd/sydneypi
Base model
black-forest-labs/FLUX.1-dev