Instructions to use LegoClipStars/Spike with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LegoClipStars/Spike with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dataautogpt3/OpenDalleV1.1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("LegoClipStars/Spike") prompt = "NEFT" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 5f1f213c88f5f13a55531111b3fc7f5753ba3ef477237c4ac4ee7d5b4a7d02e6
- Size of remote file:
- 99.2 MB
- SHA256:
- e3addb5d2082a8823116f1e14f887fd3acb9735d539587943a7c14a51d72d505
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