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 unet/diffusion_pytorch_model.bin from CompVis/ldm-text2im-large-256: direct link, hf CLI and curl.
- Browser
- Download file 3.49 GB
-
https://huggingface.co/CompVis/ldm-text2im-large-256/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://CompVis/ldm-text2im-large-256/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/CompVis/ldm-text2im-large-256/resolve/main/unet/diffusion_pytorch_model.bin
3.49 GB
- Xet hash:
- ef5d3a5001a0336901988e69cb1413d491f94a25dec29642cb58b295bcd0c0b4
- Size of remote file:
- 3.49 GB
- SHA256:
- 61459453cb8e411842ff1c109da94129f94349d46e579dbec303449aa74f07bf
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