Instructions to use SurAyush/StableEmote_LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SurAyush/StableEmote_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("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("SurAyush/StableEmote_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
Download checkpoint-3000/optimizer.bin from SurAyush/StableEmote_LoRA: direct link, hf CLI and curl.
- Browser
- Download file 3.4 MB
-
https://huggingface.co/SurAyush/StableEmote_LoRA/resolve/main/checkpoint-3000/optimizer.bin
- Command line
-
hf download hf://SurAyush/StableEmote_LoRA/checkpoint-3000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/SurAyush/StableEmote_LoRA/resolve/main/checkpoint-3000/optimizer.bin
3.4 MB
- Xet hash:
- cdb4a518318509cba0e196b33747871a2d842b5a414dca3846c3604d6a2f475a
- Size of remote file:
- 3.4 MB
- SHA256:
- c73e57734986ef093f3129f0cae491eac9a730244a2e6eb28b86ec97b357a55e
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