Instructions to use DataHoney/MagGo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DataHoney/MagGo 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("DataHoney/MagGo") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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# LoRA ファイルフォルダ / LoRA File Folder
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## 説明 / Description
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---
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license: c-uda
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library_name: diffusers
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pipeline_tag: text-to-image
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tags:
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- lora
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- flux-dev
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base_model: black-forest-labs/FLUX.1-dev
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---
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# LoRA ファイルフォルダ / LoRA File Folder
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## 説明 / Description
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