Text-to-Image
Diffusers
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use anic87/poor_well with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use anic87/poor_well with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("anic87/poor_well", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks poorly-differentiated-adenocarcinoma" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-1000/optimizer.bin from anic87/poor_well: direct link, hf CLI and curl.
- Browser
- Download file 6.88 GB
-
https://huggingface.co/anic87/poor_well/resolve/main/checkpoint-1000/optimizer.bin
- Command line
-
hf download hf://anic87/poor_well/checkpoint-1000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/anic87/poor_well/resolve/main/checkpoint-1000/optimizer.bin
6.88 GB
- Xet hash:
- d0801080d834402385befd2a8f435917fe6e3d282e3e682b99552c4874c960c5
- Size of remote file:
- 6.88 GB
- SHA256:
- 782353e5be73e5621e4c65785fe407a4787f9702f2efea9b7bf7caf748059028
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