Instructions to use Evel/YoShin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Evel/YoShin with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Evel/YoShin", 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
Commit History
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Add Diffusers weights
Add Diffusers weights converted from checkpoint `YoShin_4000.ckpt` in revision dc55b19a686c8e239610bb19dac5a2175cf1769186438a8
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enable inference widget (#1)
- enable inference widget (0b64d29c3f97513b69350da84b724e224de13721) Co-authored-by: Ahsen Khaliq <akhaliq@users.noreply.huggingface.co>dc55b19 -
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In my experience, it works better in img2img, txt2img gives snakes most of the time. This was made with dreambooth extension for Automatic 111 using 47 images and 4000 steps. License: This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage. The CreativeML OpenRAIL License specifies: You can't use the model to deliberately produce nor share illegal or harmful outputs or content The authors claims no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in the license You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully) Please read the full license herefa90d55 -
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