Instructions to use deepgoyal19/lora14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use deepgoyal19/lora14 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/lora14") 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-80/optimizer.bin from deepgoyal19/lora14: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/deepgoyal19/lora14/resolve/main/checkpoint-80/optimizer.bin
- Command line
-
hf download hf://deepgoyal19/lora14/checkpoint-80/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/deepgoyal19/lora14/resolve/main/checkpoint-80/optimizer.bin
6.59 MB
- Xet hash:
- e7b9d9ec8817b461f5d4f192da382853813ec7b3b27b1a28c2854505b4a30e50
- Size of remote file:
- 6.59 MB
- SHA256:
- 0cab5cef854fa35405eab5f84f0dad640b670235f8a36759c295cc38a659b2f7
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