Instructions to use Ridealong/Test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ridealong/Test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Ridealong/Test") prompt = "UNICODE\u0000\u0000m\u0000a\u0000l\u0000e\u0000,\u0000 \u0000r\u0000e\u0000a\u0000l\u0000i\u0000s\u0000t\u0000i\u0000c\u0000,\u0000 \u0000 \u0000p\u0000o\u0000l\u0000i\u0000c\u0000e\u0000,\u0000 \u0000 \u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000P\u0000o\u0000l\u0000i\u0000c\u0000i\u0000a\u0000M\u0000B\u0000:\u00000\u0000.\u00007\u0000>\u0000" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from Ridealong/Test: direct link, hf CLI and curl.
- Browser
- Download file 603 Bytes
-
https://huggingface.co/Ridealong/Test/resolve/main/README.md
- Command line
-
hf download hf://Ridealong/Test/README.md
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curl -L -o README.md https://huggingface.co/Ridealong/Test/resolve/main/README.md
603 Bytes
| tags: | |
| - text-to-image | |
| - stable-diffusion | |
| - lora | |
| - diffusers | |
| - template:sd-lora | |
| widget: | |
| - text: "UNICODE\0\0m\0a\0l\0e\0,\0 \0r\0e\0a\0l\0i\0s\0t\0i\0c\0,\0 \0 \0p\0o\0l\0i\0c\0e\0,\0 \0 \0<\0l\0o\0r\0a\0:\0P\0o\0l\0i\0c\0i\0a\0M\0B\0:\00\0.\07\0>\0" | |
| output: | |
| url: images/00056.jpeg | |
| base_model: stabilityai/stable-diffusion-xl-base-1.0 | |
| instance_prompt: null | |
| license: cc | |
| # PoliciaMB | |
| <Gallery /> | |
| ## Model description | |
| Brazil MP uniform | |
| ## Download model | |
| Weights for this model are available in Safetensors format. | |
| [Download](/Ridealong/Test/tree/main) them in the Files & versions tab. | |