Instructions to use thuyet/lorathuyet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use thuyet/lorathuyet 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("thuyet/lorathuyet") prompt = "**Realistic photo,thuyet,a young Asian man,15 years old,sitting on a white chair indoors,wearing a black bucket hat with a stylish embroidered logo,cinematic lighting,moody and soft tones,side profile view,focused expression,dressed in a black T-shirt,background with red and beige curtains,elegant and modern aesthetic,relaxed yet attentive posture,high-quality photography,depth of field emphasizing subject.**," image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
thuyet1.3

- Prompt
- **Realistic photo,thuyet,a young Asian man,15 years old,sitting on a white chair indoors,wearing a black bucket hat with a stylish embroidered logo,cinematic lighting,moody and soft tones,side profile view,focused expression,dressed in a black T-shirt,background with red and beige curtains,elegant and modern aesthetic,relaxed yet attentive posture,high-quality photography,depth of field emphasizing subject.**,
- Negative Prompt
- ng_deepnegative_v1_75t,(badhandv4:1.2),EasyNegative,(worst quality:2),,nsfw
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for thuyet/lorathuyet
Base model
black-forest-labs/FLUX.1-dev