Instructions to use Adminhuggingface/OUTPUTA_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Adminhuggingface/OUTPUTA_2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Adminhuggingface/OUTPUTA_2") 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-12500/pytorch_model.bin from Adminhuggingface/OUTPUTA_2: direct link, hf CLI and curl.
- Browser
- Download file 3.29 MB
-
https://huggingface.co/Adminhuggingface/OUTPUTA_2/resolve/main/checkpoint-12500/pytorch_model.bin
- Command line
-
hf download hf://Adminhuggingface/OUTPUTA_2/checkpoint-12500/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Adminhuggingface/OUTPUTA_2/resolve/main/checkpoint-12500/pytorch_model.bin
3.29 MB
- Xet hash:
- 030064d2dd7e3ff94f41a31b138da4dc0ec9409ace47344ffbf38a1c2282da04
- Size of remote file:
- 3.29 MB
- SHA256:
- b2d60c448142429769d0bdb17770f442d6532565f43fb620b28cdf4df7ab77ee
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