Instructions to use jpawan33/instruct-pix2pix-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jpawan33/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("jpawan33/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 jpawan33/instruct-pix2pix-model: direct link, hf CLI and curl.
- Browser
- Download file 6.93 GB
-
https://huggingface.co/jpawan33/instruct-pix2pix-model/resolve/main/checkpoint-5000/optimizer.bin
- Command line
-
hf download hf://jpawan33/instruct-pix2pix-model/checkpoint-5000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/jpawan33/instruct-pix2pix-model/resolve/main/checkpoint-5000/optimizer.bin
6.93 GB
- Xet hash:
- 8c324558e8b747e03e65d8ba8fe52db52776f658d707b8d77b50bfbceaf8caed
- Size of remote file:
- 6.93 GB
- SHA256:
- 2926f35cdbe09b5b174351dc4d5420fd0840b0a32b94ba99a8739dcc1b28f7f0
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