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 Settings
- Draw Things
- DiffusionBee
| license: c-uda | |
| library_name: diffusers | |
| pipeline_tag: text-to-image | |
| tags: | |
| - lora | |
| - flux-dev | |
| base_model: black-forest-labs/FLUX.1-dev | |
| Sample: | |
|  | |
| # Flux テスト用 LoRA モデル / Flux Test LoRA Model | |
| ## 説明 / Description | |
| これは Flux テスト用の LoRA モデルで、**MagGo** の画像を生成できます。 | |
| 現在は **初期テスト段階** にありますので、テスト対象や LoRA の設定重みを自由に調整してください。 | |
| This is a Flux test LoRA model that can generate **MagGo** images. | |
| Currently, it is in the **initial testing phase**, so please freely adjust the test subject and LoRA weight settings. | |
| ## 使用方法 / How to Use | |
| - Flux 関連のテスト用途に適しています。 | |
| - 生成される画像には多少の誤差が生じる可能性があります。 | |
| - LoRA の重みを調整して最適な結果を得てください。 | |
| Suitable for Flux-related testing. | |
| Generated images may have some variation. | |
| Adjust the LoRA weight to achieve optimal results. |