Instructions to use mann-e/mann-e_4_rev-1-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mann-e/mann-e_4_rev-1-3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mann-e/mann-e_4_rev-1-3", 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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# Mann-E 4 (revision 1.3)
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## Samples (with prompts)
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# Mann-E 4 (revision 1.3)
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_Mann-E_ (which is read Mani or in Persian مانی) is a state-of-the-art AI art generator made by [Muhammadreza Haghiri](https://haghiri75.com/en) as a part of [Open Cognitives](https://opencognitives.com) projects. The goal of this project was to bring a Free/Libre and Open Source (FLOSS for short) equivalent of [Midjourney](https://midjourney.com). This model is based on [Stable Diffusion 1.5](https://huggingface.co/runwayml/stable-diffusion-v1-5) and the data gathered from the internet and also has its own unique text encoder.
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## Colab Access
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Clink on [this link](https://colab.research.google.com/github/prp-e/mann-e/blob/main/Mann_E.ipynb) to accesss our web user interface through colab.
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## Samples (with prompts)
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