Instructions to use gfalcao/early-fire-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gfalcao/early-fire-generator with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("gfalcao/early-fire-generator", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Run the text-to-image model by writting the special prompt "smkfr". When using it in an image-to-image pipeline, always include the special token "smkfr"
This model is trained over Stable Diffusion 2.1 To run this on an image-to-image pipeline check this: https://huggingface.co/docs/diffusers/main/en/using-diffusers/img2img
- Downloads last month
- 13