Instructions to use AML-group10/lora-output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AML-group10/lora-output with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("segmind/tiny-sd", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("AML-group10/lora-output") 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
Download image_0.png from AML-group10/lora-output: direct link, hf CLI and curl.
- Browser
- Download file 361 kB
-
https://huggingface.co/AML-group10/lora-output/resolve/main/image_0.png
- Command line
-
hf download hf://AML-group10/lora-output/image_0.png
-
curl -L -o image_0.png https://huggingface.co/AML-group10/lora-output/resolve/main/image_0.png
361 kB

- Xet hash:
- 4e1445a634fd34b35193d4f9ac33b28425cd8198c76e73a277f17e1a2179c740
- Size of remote file:
- 361 kB
- SHA256:
- bdcefe7d96b653bd11cf04d7d5e90fc50955c13aeb3ad6ae8ce2e1db7c05c7c8
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