Instructions to use glif/anime-blockprint-style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use glif/anime-blockprint-style with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("glif/anime-blockprint-style") prompt = "A young man with glasses, slightly messy hair, and a thoughtful expression, portrait, blockprint style" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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README.md
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*This LoRA is a part of the Glif Loradex Trainer project. The goal of the project is to explore different training techniques together, create and release opensource LoRAs, and fill the world with more art. This project is sponsored by [Glif](https://glif.app/), offering free early access to Flux Dev training on the Glif Discord.*
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*All models in the Loradex Trainer program are released under the
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## Trigger words
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*This LoRA is a part of the Glif Loradex Trainer project. The goal of the project is to explore different training techniques together, create and release opensource LoRAs, and fill the world with more art. This project is sponsored by [Glif](https://glif.app/), offering free early access to Flux Dev training on the Glif Discord.*
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*All models in the Loradex Trainer program are released under the BFL Flux Dev license. Attribution for the original LoRA creator is always appreciated!*
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## Trigger words
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