Instructions to use AnvitT/pikachu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AnvitT/pikachu with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AnvitT/pikachu", 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
Upload the concept Pikachu! embeds and token
Browse files
README.md
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---
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license: creativeml-openrail-m
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tags:
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- NxtWave-GenAI-Webinar
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- text-to-image
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- stable-diffusion
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---
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### Pikachu! Dreambooth model trained by AnvitT following the "Build your own Gen AI model" session by NxtWave.
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Project Submission Code: IIITB-147
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Sample pictures of this concept:
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xzg.ckpt
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version https://git-lfs.github.com/spec/v1
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oid sha256:f171052c8cbf2289f17bf0b5abd6d17bcb380320d2eb2fc2ed006c247da2dc82
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size 2132780794
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