Instructions to use mostlywinnie/hannah-rebuilt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mostlywinnie/hannah-rebuilt 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("mostlywinnie/hannah-rebuilt") prompt = "Hannah2" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Hannah Rebuilt
A Flux LoRA trained on a local computer with Fluxgym
Trigger words
You should use Hannah2 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 mostlywinnie/hannah-rebuilt
Base model
black-forest-labs/FLUX.1-dev