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:
- a6f14248f9faf70f6cacab26a813373d9b444c428f9d06e64c26e66b05072953
- Size of remote file:
- 295 MB
- SHA256:
- 7921507dcd5722d4621ed94a05e36f6cb59fd32ae3c16daea38d4683c1652953
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