Stable-diffusion-v1-5 Huggingface Download __hot__: Runwayml

pip install --upgrade diffusers transformers scipy torch

Hugging Face requires user authentication for gated models:

from diffusers import StableDiffusionPipeline runwayml stable-diffusion-v1-5 huggingface download

pipe = StableDiffusionPipeline.from_pretrained("./stable-diffusion-v1-5", torch_dtype=torch.float16) pipe.to("cuda") image = pipe("a photograph of an astronaut riding a horse").images[0] image.save("test_output.png") print("Model works correctly.")

Single-file checkpoint (if using original .ckpt): v1-5-pruned-emaonly.ckpt Access requires a registered account and acceptance of

| Error | Cause | Solution | |-------|-------|----------| | 401 Client Error | Missing/invalid token | Run huggingface-cli login | | Gated model error | License not accepted | Visit model page, click "Agree and access" | | LFS file not downloaded | git-lfs not installed | git lfs install then git lfs pull | | Out of disk space | ~10 GB required | Clear cache or use symlink mode | | Connection timeout | Network instability | Use resume_download=True in Python |

Users must adhere to the integrated into the Diffusers library, which attempts to filter out NSFW or offensive content. Because the model was trained on broad internet data, it may reflect societal biases or generate sensitive content if the safety filters are bypassed. Stable Diffusion v1

The model is primarily hosted on Hugging Face. Access requires a registered account and acceptance of the model license terms.

Since the repository is now "gated," you cannot simply copy-paste a download link. You must authenticate your environment with Hugging Face.

Stable Diffusion v1.5 is a latent text-to-image diffusion model released by RunwayML in collaboration with Stability AI and CompVis. This report details the technical specifications, access methods via Hugging Face, and implementation requirements for researchers and developers. 1. Model Overview