Instructions to use ankush10010/SD1.5_distilled_attentionlayer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ankush10010/SD1.5_distilled_attentionlayer with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ankush10010/SD1.5_distilled_attentionlayer", 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 checkpoint-4000/model.safetensors from ankush10010/SD1.5_distilled_attentionlayer: direct link, hf CLI and curl.
- Browser
- Download file 2.32 GB
-
https://huggingface.co/ankush10010/SD1.5_distilled_attentionlayer/resolve/main/checkpoint-4000/model.safetensors
- Command line
-
hf download hf://ankush10010/SD1.5_distilled_attentionlayer/checkpoint-4000/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ankush10010/SD1.5_distilled_attentionlayer/resolve/main/checkpoint-4000/model.safetensors
2.32 GB
- Size of remote file:
- 2.32 GB
- SHA256:
- 59693048d29e630df219a24442442e64d9b22998f5e3c0ca43bf3497087e5145
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