Instructions to use RodrigoFlorencio/flucasx-treinado with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RodrigoFlorencio/flucasx-treinado 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-schnell", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("RodrigoFlorencio/flucasx-treinado") prompt = "A realistic IPhone 15 selfie of FluxTLucas" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
flucasx-treinado
Model trained with AI Toolkit by Ostris

- Prompt
- A realistic IPhone 15 selfie of FluxTLucas

- Prompt
- A cinematic shot of FluxTLucas driving in high speed

- Prompt
- A FluxTLucas riding a flying white horse in a sundown sky
Trigger words
You should use FluxTLucas 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-schnell', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('RodrigoFlorencio/flucasx-treinado', weight_name='flucasx-treinado')
image = pipeline('A realistic IPhone 15 selfie of FluxTLucas').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 RodrigoFlorencio/flucasx-treinado
Base model
black-forest-labs/FLUX.1-schnell