You probably do not need this unless you are training your own IP Adapters.

Modified version of the vision encoder of [CLIP-ViT-H-14-laion2B-s32B-b79K](https://huggingface.co/laion/CLIP-ViT-H-14-laion2B-s32B-b79K) to handle 448 x 448 inputs 
vs the original 224 x 224 inputs. It will probbaly not work for classification (as is), but will DIP work for for IP+ adapters that use CLIP-ViT-H, though they will need to be
fine tuned a little more. 

Hidden layer outputs go from `(257, 1280)` to `(1025, 1280)`, which can be digested by the Resampler without modification or weight resizing.
{"license": "mit", "library_name": "transformers", "pipeline_tag": "zero-shot-image-classification"}
transformers safetensors clip_vision_model zero-shot-image-classification license:mit endpoints_compatible region:us