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
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Download diffusers/docs/source/en/api/internal_classes_overview.md from elvis92/pets_rank_2: direct link, hf CLI and curl.
- Browser
- Download file 926 Bytes
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https://huggingface.co/elvis92/pets_rank_2/resolve/main/diffusers/docs/source/en/api/internal_classes_overview.md
- Command line
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hf download hf://elvis92/pets_rank_2/diffusers/docs/source/en/api/internal_classes_overview.md
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curl -L -o internal_classes_overview.md https://huggingface.co/elvis92/pets_rank_2/resolve/main/diffusers/docs/source/en/api/internal_classes_overview.md
926 Bytes
Overview
The APIs in this section are more experimental and prone to breaking changes. Most of them are used internally for development, but they may also be useful to you if you're interested in building a diffusion model with some custom parts or if you're interested in some of our helper utilities for working with 🤗 Diffusers.