Instructions to use elvis92/pets_rank_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use elvis92/pets_rank_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("elvis92/pets_rank_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 diffusers/examples/custom_diffusion/requirements.txt from elvis92/pets_rank_2: direct link, hf CLI and curl.
- Browser
- Download file 68 Bytes
-
https://huggingface.co/elvis92/pets_rank_2/resolve/main/diffusers/examples/custom_diffusion/requirements.txt
- Command line
-
hf download hf://elvis92/pets_rank_2/diffusers/examples/custom_diffusion/requirements.txt
-
curl -L -o requirements.txt https://huggingface.co/elvis92/pets_rank_2/resolve/main/diffusers/examples/custom_diffusion/requirements.txt
68 Bytes
| accelerate | |
| torchvision | |
| transformers>=4.25.1 | |
| ftfy | |
| tensorboard | |
| Jinja2 | |