Instructions to use EarthnDusk/IsometricFuture with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EarthnDusk/IsometricFuture with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("EarthnDusk/IsometricFuture", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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Download README.md from EarthnDusk/IsometricFuture: direct link, hf CLI and curl.
- Browser
- Download file 286 Bytes
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https://huggingface.co/EarthnDusk/IsometricFuture/resolve/main/README.md
- Command line
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hf download hf://EarthnDusk/IsometricFuture/README.md
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curl -L -o README.md https://huggingface.co/EarthnDusk/IsometricFuture/resolve/main/README.md
286 Bytes
| license: creativeml-openrail-m | |
| language: | |
| - en | |
| library_name: diffusers | |
| # Isometric Futures | |
| Sadly this is not a diffusers one trained at hugging face and we don't understand how to import that stuff yet. | |
| But this is trained via https://github.com/TheLastBen/fast-stable-diffusion |