Instructions to use baricevic/instruct-pix2pix-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use baricevic/instruct-pix2pix-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("baricevic/instruct-pix2pix-model", 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 vae/diffusion_flax_model.msgpack from baricevic/instruct-pix2pix-model: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/baricevic/instruct-pix2pix-model/resolve/main/vae/diffusion_flax_model.msgpack
- Command line
-
hf download hf://baricevic/instruct-pix2pix-model/vae/diffusion_flax_model.msgpack
-
curl -L -o diffusion_flax_model.msgpack https://huggingface.co/baricevic/instruct-pix2pix-model/resolve/main/vae/diffusion_flax_model.msgpack
167 MB
- Xet hash:
- 9d5fb99a551abc65380fd9775b7eb507471f354f91c3e85268bb9593b2c56f24
- Size of remote file:
- 167 MB
- SHA256:
- 0e3e81680c6669960f086eca278c8a1f89dd2ed7eadef806e049b56e426c1809
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