Instructions to use Bbneek/Neeko_tesr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Bbneek/Neeko_tesr with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-2512", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Bbneek/Neeko_tesr") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| tags: | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - template:diffusion-lora | |
| widget: | |
| - output: | |
| url: images/1(18).png | |
| text: '-' | |
| base_model: Qwen/Qwen-Image-2512 | |
| instance_prompt: N33ko | |
| # N33ko | |
| <Gallery /> | |
| ## Model description | |
| N33ko test | |
| ## Trigger words | |
| You should use `N33ko` to trigger the image generation. | |
| ## Download model | |
| [Download](/Bbneek/Neeko_tesr/tree/main) them in the Files & versions tab. | |