Instructions to use mobled37/vae-model-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mobled37/vae-model-finetuned with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mobled37/vae-model-finetuned", dtype=torch.bfloat16, device_map="cuda") 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-20000/optimizer.bin from mobled37/vae-model-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 4.54 MB
-
https://huggingface.co/mobled37/vae-model-finetuned/resolve/main/checkpoint-20000/optimizer.bin
- Command line
-
hf download hf://mobled37/vae-model-finetuned/checkpoint-20000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/mobled37/vae-model-finetuned/resolve/main/checkpoint-20000/optimizer.bin
4.54 MB
- Xet hash:
- 9ab5c7988a65f4e937f7530e376b9556de67f11e95e76ecfb6c4134b3c4388bb
- Size of remote file:
- 4.54 MB
- SHA256:
- 271ab9de8c5e23d1e7fc27ccc80b70e652a9d20b1ce99062b2922f77a680a637
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.