Instructions to use deepgoyal19/lora15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use deepgoyal19/lora15 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("deepgoyal19/mysd1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("deepgoyal19/lora15") 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 checkpoint-160/optimizer.bin from deepgoyal19/lora15: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/deepgoyal19/lora15/resolve/main/checkpoint-160/optimizer.bin
- Command line
-
hf download hf://deepgoyal19/lora15/checkpoint-160/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/deepgoyal19/lora15/resolve/main/checkpoint-160/optimizer.bin
6.59 MB
- Xet hash:
- 13ba4e597ea1b0aa1e3a81a78974f1bbfd53e355be068f67d9325187e29f2667
- Size of remote file:
- 6.59 MB
- SHA256:
- 58517e6b444154d37ef75c9e4999b4ec639d1fa8917e2a22b1414160ed2168e1
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