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:
- 4e143849e16c57f30f12d7ec178115bcbfb6aedfb2143e2ea6eea13910e46279
- Size of remote file:
- 295 MB
- SHA256:
- d5771b803045cebaf4446bd9b2070500f3b2593b448384ed40b998bef5277651
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