Instructions to use hyperr1se/lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hyperr1se/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("undefined", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("hyperr1se/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
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Download README.md from hyperr1se/lora: direct link, hf CLI and curl.
- Browser
- Download file 531 Bytes
-
https://huggingface.co/hyperr1se/lora/resolve/main/README.md
- Command line
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hf download hf://hyperr1se/lora/README.md
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curl -L -o README.md https://huggingface.co/hyperr1se/lora/resolve/main/README.md
531 Bytes
| tags: | |
| - flux | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - fal | |
| base_model: undefined | |
| instance_prompt: | |
| license: other | |
| # lora | |
| <Gallery /> | |
| ## Model description | |
| ## Trigger words | |
| You should use `` to trigger the image generation. | |
| ## Download model | |
| Weights for this model are available in Safetensors format. | |
| [Download](/hyperr1se/lora/tree/main) them in the Files & versions tab. | |
| ## Training at fal.ai | |
| Training was done using [fal.ai/models/fal-ai/wan-22-image-trainer](https://fal.ai/models/fal-ai/wan-22-image-trainer). | |