Text-to-Image
Diffusers
TensorBoard
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
textual_inversion
Instructions to use hangeol/3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hangeol/3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_textual_inversion("hangeol/3") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download learned_embeds-steps-1000.bin from hangeol/3: direct link, hf CLI and curl.
- Browser
- Download file 16.3 kB
-
https://huggingface.co/hangeol/3/resolve/main/learned_embeds-steps-1000.bin
- Command line
-
hf download hf://hangeol/3/learned_embeds-steps-1000.bin
-
curl -L -o learned_embeds-steps-1000.bin https://huggingface.co/hangeol/3/resolve/main/learned_embeds-steps-1000.bin
16.3 kB
- Xet hash:
- 23e79051df4ad42f850ae023591ed3806a21a3fe1431e5b5708b907c64e0c33c
- Size of remote file:
- 16.3 kB
- SHA256:
- 45216fe87fe156ab07c6cdf63fe11f1370ffd25bf7ba023dc17ba7131286e1bc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.