Instructions to use umaruchain/instruct-pix2pix-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use umaruchain/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("umaruchain/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-4000/optimizer.bin from umaruchain/instruct-pix2pix-model: direct link, hf CLI and curl.
- Browser
- Download file 6.88 GB
-
https://huggingface.co/umaruchain/instruct-pix2pix-model/resolve/main/checkpoint-4000/optimizer.bin
- Command line
-
hf download hf://umaruchain/instruct-pix2pix-model/checkpoint-4000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/umaruchain/instruct-pix2pix-model/resolve/main/checkpoint-4000/optimizer.bin
6.88 GB
- Xet hash:
- 64cbf944eeacde15774fc6e5eacc23c5f9010fbbbe8d1947be9be795868f59e7
- Size of remote file:
- 6.88 GB
- SHA256:
- 7c5f1cf5e4274a53e2beb8712e24d0733f52a19d6d74dd37aa7983ba4a82daff
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