Image-to-Image
Diffusers
Safetensors
flux
semantic-segmentation
instance-segmentation
referring-segmentation
depth-estimation
surface-normal-estimation
image-editing
text-to-image
Instructions to use FunAILab/Open-Vision-Banana with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FunAILab/Open-Vision-Banana with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FunAILab/Open-Vision-Banana", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Model card: task collage, editing and generation prompts, LoRA adapters
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Outputs of the zero-shot 9B model on an in-the-wild photo, with the summarised prompt below each output.
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## 📦 Checkpoints
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Outputs of the zero-shot 9B model on an in-the-wild photo, with the summarised prompt below each output.
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## 📦 Checkpoints
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