Instructions to use emilianJR/Anyh91 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use emilianJR/Anyh91 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("emilianJR/Anyh91", 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 emilianJR/Anyh91: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/emilianJR/Anyh91/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://emilianJR/Anyh91/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/emilianJR/Anyh91/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- cc93b273cba62cf7358430737885fd8f3dc16028ea81e67928c6e7220d54f4c0
- Size of remote file:
- 492 MB
- SHA256:
- cd000432633bfa95d9560115c319b76a7bcc251f9f9a0e680190c071034d2e2c
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