Instructions to use zero-jin/instruct-pix2pix-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zero-jin/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("zero-jin/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 checkpoint-5000/optimizer.bin from zero-jin/instruct-pix2pix-model: direct link, hf CLI and curl.
- Browser
- Download file 6.93 GB
-
https://huggingface.co/zero-jin/instruct-pix2pix-model/resolve/main/checkpoint-5000/optimizer.bin
- Command line
-
hf download hf://zero-jin/instruct-pix2pix-model/checkpoint-5000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/zero-jin/instruct-pix2pix-model/resolve/main/checkpoint-5000/optimizer.bin
6.93 GB
- Xet hash:
- 3468c5a3ccc6b1e7194f9aa84ba8a309d27f5a74dd722c1d6620f20ef9993a9c
- Size of remote file:
- 6.93 GB
- SHA256:
- 6538062f77349551bdd15fc30bee1567c6ffd24a94b20781092de5ed7419687b
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