Instructions to use AMead10/epicloot-qwen-2-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AMead10/epicloot-qwen-2-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("Qwen/Qwen-Image", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("AMead10/epicloot-qwen-2-lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- c467d341b15e8f22bf650d052f2d7e82986a5f08e74182837b58351eed672005
- Size of remote file:
- 295 MB
- SHA256:
- 86033e6a7f977a4be3bca851c298beebda220f4523ad18a2c81184f0636c94a9
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