Instructions to use Fazeex/vase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Fazeex/vase with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Fazeex/vase", 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 vase 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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### vase Dreambooth model trained by Fazeex following the "Build your own Gen AI model" session by NxtWave.
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Project Submission Code: AEC--730221104002
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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 sha256:1a2c4a82d28e90a80e23f5986e0c2445af6a3c30c48f2580a51e4b97bb9df618
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size 2132781219
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