Instructions to use RhaegarKhan/OMI_LORA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RhaegarKhan/OMI_LORA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("HiDream-ai/HiDream-I1-Full", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("RhaegarKhan/OMI_LORA") prompt = "cat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
omi_lora

- Prompt
- cat
Model description
lora trained using OneTrainer having alpha weights for hidream
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for RhaegarKhan/OMI_LORA
Base model
HiDream-ai/HiDream-I1-Full