Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
art
stable-diffusion
pokemon
fine-tuned
non-commercial
research
Instructions to use PPPPPilot/StableDiffusionPokemon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PPPPPilot/StableDiffusionPokemon with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("PPPPPilot/StableDiffusionPokemon", 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
- Draw Things
- DiffusionBee
Update README.md
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README.md
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from diffusers import StableDiffusionPipeline
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pipe = StableDiffusionPipeline.from_pretrained("PPPPPilot/StableDiffusionPokemon")
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image = pipe("a cute pokemon character").images[0]
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from diffusers import StableDiffusionPipeline
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pipe = StableDiffusionPipeline.from_pretrained("PPPPPilot/StableDiffusionPokemon")
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image = pipe("a cute pokemon character").images[0]
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image.save("my_pokemon.png")
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```
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## ✍🏼 Technical Specification
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Dataset: reach-vb/pokemon-blip-captions
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Training Steps: 10,000
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Evaluation Score: FID 60.19, CLIP 0.235
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License: CreativeML Open RAIL-M (Non-commercial)
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