Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use digiplay/bra_v40_diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use digiplay/bra_v40_diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("digiplay/bra_v40_diffusers", 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.fp16.bin from digiplay/bra_v40_diffusers: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/digiplay/bra_v40_diffusers/resolve/main/text_encoder/pytorch_model.fp16.bin
- Command line
-
hf download hf://digiplay/bra_v40_diffusers/text_encoder/pytorch_model.fp16.bin
-
curl -L -o pytorch_model.fp16.bin https://huggingface.co/digiplay/bra_v40_diffusers/resolve/main/text_encoder/pytorch_model.fp16.bin
246 MB
- Xet hash:
- ee6ddc66288c0b6fd94fc88d1c9c857fb483a14c39364031a22dcb2398a0120c
- Size of remote file:
- 246 MB
- SHA256:
- 9a3513398f78cb973d5118dadbb8118a93380f3641eb6499ba531907efddaaf3
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