Instructions to use ksj47/sonu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ksj47/sonu with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ksj47/sonu", 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
Upload the concept Sonu 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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### Sonu Dreambooth model trained by ksj47 following the "Build your own Gen AI model" session by NxtWave.
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Project Submission Code: Nil
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Sample pictures of this concept:
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sonu.ckpt
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version https://git-lfs.github.com/spec/v1
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oid sha256:6e7b06111810fb80e36aa868e3981a369eac54dda69299307515da2d8910b8a2
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size 2132782354
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