Instructions to use wikeeyang/Flux2-Klein-9B-True-V3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wikeeyang/Flux2-Klein-9B-True-V3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wikeeyang/Flux2-Klein-9B-True-V3", 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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您可以尝试一下全新的 ComfyUI GGUF 模型加载插件 [**smthemex/ComfyUI_Dif_GGUF**](https://github.com/smthemex/ComfyUI_Dif_GGUF),它能适配更多的 GGUF 文件格式,并且将很快集成低显存(4-8GB)显卡的 GGUF 模型块卸载管理能力。
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Recommend to try the new GGUF ComfyUI loader plugin, [**smthemex/ComfyUI_Dif_GGUF**](https://github.com/smthemex/ComfyUI_Dif_GGUF), it compatible with more GGUF format, and will add low VRAM (4-8GB) management for GGUF soon.
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针对低显存的用户,推荐 [**smthemex/ComfyUI_UniBlockSwap**](https://github.com/smthemex/ComfyUI_UniBlockSwap),只需 **4-6GB** 显存,即可跑 bf16 全量模型。
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Recommend [**smthemex/ComfyUI_UniBlockSwap**](https://github.com/smthemex/ComfyUI_UniBlockSwap) plugin for LOW VRAM users, it only requires **4-6GB** of VRAM to run the full bf16 model.
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您可以尝试一下全新的 ComfyUI GGUF 模型加载插件 [**smthemex/ComfyUI_Dif_GGUF**](https://github.com/smthemex/ComfyUI_Dif_GGUF),它能适配更多的 GGUF 文件格式,并且将很快集成低显存(4-8GB)显卡的 GGUF 模型块卸载管理能力。
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Recommend to try the new GGUF ComfyUI loader plugin, [**smthemex/ComfyUI_Dif_GGUF**](https://github.com/smthemex/ComfyUI_Dif_GGUF), it compatible with more GGUF format, and will add low VRAM (4-8GB) management for GGUF soon.
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