Instructions to use SimonDL/ip2p-tt-model-1e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SimonDL/ip2p-tt-model-1e with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SimonDL/ip2p-tt-model-1e", 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-200/optimizer.bin from SimonDL/ip2p-tt-model-1e: direct link, hf CLI and curl.
- Browser
- Download file 1.75 GB
-
https://huggingface.co/SimonDL/ip2p-tt-model-1e/resolve/main/checkpoint-200/optimizer.bin
- Command line
-
hf download hf://SimonDL/ip2p-tt-model-1e/checkpoint-200/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/SimonDL/ip2p-tt-model-1e/resolve/main/checkpoint-200/optimizer.bin
1.75 GB
- Xet hash:
- eb6e7dcb08beaa74d6f28de1a2d2ce59131b36e02b691af9f3efbc3c5a85fae7
- Size of remote file:
- 1.75 GB
- SHA256:
- 4a2d6c4547e08c6965e31057e91ffaae5f366e668fabcc8934a0e2b779fe657a
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