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
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Download README.md from LegoClipStars/Spike: direct link, hf CLI and curl.
- Browser
- Download file 610 Bytes
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https://huggingface.co/LegoClipStars/Spike/resolve/main/README.md
- Command line
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hf download hf://LegoClipStars/Spike/README.md
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curl -L -o README.md https://huggingface.co/LegoClipStars/Spike/resolve/main/README.md
610 Bytes
| tags: | |
| - text-to-image | |
| - stable-diffusion | |
| - lora | |
| - diffusers | |
| - template:sd-lora | |
| widget: | |
| - text: NEFT | |
| parameters: | |
| negative_prompt: flying dragon | |
| output: | |
| url: images/Spike_%28My_Little_Pony%29.png | |
| base_model: dataautogpt3/OpenDalleV1.1 | |
| instance_prompt: Please spare me | |
| license: cc-by-4.0 | |
| # Spike | |
| <Gallery /> | |
| ## Model description | |
| Here's the RVC (700 epoch) voice model of Spike the dragon from MLP:FIM | |
| ## Trigger words | |
| You should use `Please spare me` to trigger the image generation. | |
| ## Download model | |
| [Download](/LegoClipStars/Spike/tree/main) them in the Files & versions tab. | |