Instructions to use scrapware/amanivae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use scrapware/amanivae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Lykon/AnyLoRA", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("scrapware/amanivae") prompt = " amanivae " image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| tags: | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - template:diffusion-lora | |
| widget: | |
| - text: ' amanivae ' | |
| parameters: | |
| negative_prompt: >- | |
| amqnivae.pt (Bluewish) | |
| output: | |
| url: images/realametta_v2012HQ_amanivae.png | |
| - text: ' amenivae ' | |
| parameters: | |
| negative_prompt: >- | |
| amenivae (Neutral Colored) | |
| output: | |
| url: images/realametta_v2012HQ_amenivae.png | |
| - text: ' animevae ' | |
| parameters: | |
| negative_prompt: >- | |
| Sample of animevae.pt original. | |
| output: | |
| url: images/realametta_v2012HQ_animevae.png | |
| base_model: Lykon/AnyLoRA | |
| instance_prompt: null | |
| license: openrail | |
| # amanivae | |
| <Gallery /> | |
| ## Model description | |
| Neutral colored animevae only animevae(100%) on feat latest floating tensor genetic shift technology. half size pruned to only state_dict(rest keep loss_logver). | |
| <b>Amanivae:</b> bluewish</ br> | |
| <b>Amenivae:</b> Neutral Colored<b> | |
| <b>(!) Adjust with some rate(0.1-0.9) from animevae.pt original.</b> | |
| ## Download model | |
| Weights for this model are available in Safetensors format. | |
| [Download](/scrapware/amanivae/tree/main) them in the Files & versions tab. | |