Instructions to use bglick13/hopper-medium-v2-value-function-hor32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bglick13/hopper-medium-v2-value-function-hor32 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("bglick13/hopper-medium-v2-value-function-hor32", 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
Download unet/diffusion_pytorch_model.bin from bglick13/hopper-medium-v2-value-function-hor32: direct link, hf CLI and curl.
- Browser
- Download file 15.9 MB
-
https://huggingface.co/bglick13/hopper-medium-v2-value-function-hor32/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://bglick13/hopper-medium-v2-value-function-hor32/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/bglick13/hopper-medium-v2-value-function-hor32/resolve/main/unet/diffusion_pytorch_model.bin
15.9 MB
- Xet hash:
- 231419407de54297e02aacad5f565cf3f33373d10401b64361b19b24f4f5c49d
- Size of remote file:
- 15.9 MB
- SHA256:
- 48de376b5e024b235c01eff06e26f3f9dafe1350c5883859328f1aa4b41bf2ea
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.