Instructions to use Rand000mGuy/amara with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Rand000mGuy/amara with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Lakonik/AsymFLUX.2-klein-9B", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Rand000mGuy/amara") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 353 Bytes
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tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/c1a35cae-8cdd-4e65-97c2-1f98c333ac62.jpeg
text: '-'
base_model: Lakonik/AsymFLUX.2-klein-9B
instance_prompt: null
---
# amara
<Gallery />
## Download model
[Download](/Rand000mGuy/amara/tree/main) them in the Files & versions tab.
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