Instructions to use CompVis/ldm-text2im-large-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CompVis/ldm-text2im-large-256 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/ldm-text2im-large-256", 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 vqvae/diffusion_pytorch_model.bin from CompVis/ldm-text2im-large-256: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/CompVis/ldm-text2im-large-256/resolve/refs%2Fpr%2F2/vqvae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://CompVis/ldm-text2im-large-256@refs/pr/2/vqvae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/CompVis/ldm-text2im-large-256/resolve/refs%2Fpr%2F2/vqvae/diffusion_pytorch_model.bin
343 MB
- Xet hash:
- 30b2bc9ebd9c69ab985ba622e0f7e0b91d661b6ec9ff01d1c7b939a3f9976791
- Size of remote file:
- 343 MB
- SHA256:
- 0c2953d1dbaa0b45217adada7507d214ef5b97f0d7f3b85ec920016f3c300e8b
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