Instructions to use Envvi/Inkpunk-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Envvi/Inkpunk-Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Envvi/Inkpunk-Diffusion", 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
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license: creativeml-openrail-m
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language:
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tags:
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- stable-diffusion
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- text-to-image
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- diffusers
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---
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# Inkpunk Diffusion
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license: creativeml-openrail-m
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language:
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- pt
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tags:
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- stable-diffusion
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- text-to-image
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- diffusers
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datasets:
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- HuggingFaceH4/ultrachat_200k
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metrics:
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- accuracy
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- bleu
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library_name: adapter-transformers
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pipeline_tag: video-classification
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# Inkpunk Diffusion
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