Instructions to use Allenbv/aimersd2-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Allenbv/aimersd2-5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Allenbv/aimersd2-5", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from Allenbv/aimersd2-5: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/Allenbv/aimersd2-5/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Allenbv/aimersd2-5@refs/pr/2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Allenbv/aimersd2-5/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- 6d1286728af64a10907ea382a96b6c5bf13c6a6783bd6dcca707fa2382a0c914
- Size of remote file:
- 681 MB
- SHA256:
- f988248177fc727cf066267b3ccb62e7a74b7e3c5b3efa8a701d563e0f0ea037
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