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-13500/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-13500/pytorch_model.bin
- Command line
-
hf download hf://Adminhuggingface/OUTPUTA_2/checkpoint-13500/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Adminhuggingface/OUTPUTA_2/resolve/main/checkpoint-13500/pytorch_model.bin
3.29 MB
- Xet hash:
- cf97cdc652f5fc0c55ed688bf41b236e5ff1e09c4ef216a808167dedede52077
- Size of remote file:
- 3.29 MB
- SHA256:
- 012aa35466729a978b470d4133eb61ddd40d7aa21b445c341bd0bc0cb0fb41c5
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