Instructions to use Abahargadon/sks_sam2000V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Abahargadon/sks_sam2000V1 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("Abahargadon/sks_sam2000V1") prompt = " portrait d'une jeune femme rousse" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
sks_sam2000V1

- Prompt
- portrait d'une jeune femme rousse
Model description
Trigger words
You should use sks_sam to trigger the image generation.
Download model
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Model tree for Abahargadon/sks_sam2000V1
Base model
black-forest-labs/FLUX.1-dev