Instructions to use danbrown/testman-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use danbrown/testman-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("danbrown/AnyLora-v1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("danbrown/testman-lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- ee8ad31d80f404db7b0f111f76c3a499fb38da7d79fc00374d667d9a00286ed4
- Size of remote file:
- 6.59 MB
- SHA256:
- fa757b36b3004ee36d5795ec1d4a8d96c6f93ebabefd4b0503a47936f0461cad
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