Instructions to use VHKE/IXAR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VHKE/IXAR 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("VHKE/IXAR") prompt = "3D PIXAR BEVER walking in a forest --d 45" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
3D PIXAR BEVER
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- 3D PIXAR BEVER walking in a forest --d 45

- Prompt
- 3D PIXAR BEVER is riding a bike --d 42

- Prompt
- 3D PIXAR BEVER walking as a body builder --d 42

- Prompt
- 3D PIXAR BEVER as a rock star --d 42
Trigger words
You should use 3D PIXAR BEVER to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, Forge, etc.
Weights for this model are available in Safetensors format.
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Model tree for VHKE/IXAR
Base model
black-forest-labs/FLUX.1-dev