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Change in ip-adapter docs. CLIPVisionModelWithProjection should be im… (#6597)

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Change in ip-adapter docs. CLIPVisionModelWithProjection should be imported from transformers, not diffusers
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JuanCarlosPi
2024-01-16 11:18:13 -05:00
committed by GitHub
parent 8842bcadb9
commit dff35a86e4
1 changed files with 2 additions and 1 deletions
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docs/source/en/using-diffusers/loading_adapters.md
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@@ -344,7 +344,8 @@ pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-a
IP-Adapter relies on an image encoder to generate the image features, if your IP-Adapter weights folder contains a "image_encoder" subfolder, the image encoder will be automatically loaded and registered to the pipeline. Otherwise you can so load a [`~transformers.CLIPVisionModelWithProjection`] model and pass it to a Stable Diffusion pipeline when you create it.
```py
from diffusers import AutoPipelineForText2Image, CLIPVisionModelWithProjection
from diffusers import AutoPipelineForText2Image
from transformers import CLIPVisionModelWithProjection
import torch
image_encoder = CLIPVisionModelWithProjection.from_pretrained(