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:
- 1e35cccbe160e0e74b11a519ac9b08bf404388d52a78a0cc0a569911caa5fb8e
- Size of remote file:
- 295 MB
- SHA256:
- d42208a7a55afabee300be73dfb359f896febd1062611934d7ae9b30579a0d3d
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