Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use HumpyDonkey/dreambooth-lik-cup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use HumpyDonkey/dreambooth-lik-cup with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("HumpyDonkey/dreambooth-lik-cup", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of lik cup" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-2000/optimizer.bin from HumpyDonkey/dreambooth-lik-cup: direct link, hf CLI and curl.
- Browser
- Download file 1.73 GB
-
https://huggingface.co/HumpyDonkey/dreambooth-lik-cup/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://HumpyDonkey/dreambooth-lik-cup/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/HumpyDonkey/dreambooth-lik-cup/resolve/main/checkpoint-2000/optimizer.bin
1.73 GB
- Xet hash:
- a5361bb27240512c1ce42055befbec3375bf8a408df4696d234db469e798b158
- Size of remote file:
- 1.73 GB
- SHA256:
- 58fdbc147fcaba0dad53a2df2e479518760d638b5d233632e1ba388cd0f8b00c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.