Ablations
Collection
playing with k and rho
•
27 items
•
Updated
Model Initialized from openai/clip-vit-large-patch14
. The image encoder is finetuned with FARE at $\epsilon=2/255$. The text encoder is finetuned with LEAF at $k=1$ with $\rho=50$ and semantic constraints.
To load this model use:
from transformers import CLIPProcessor, CLIPModel
model_name = "LEAF-CLIP/CLIP-ViT-L-rho50-k1-FARE2"
processor_name = "openai/clip-vit-large-patch14"
model = CLIPModel.from_pretrained(model_name)
processor = CLIPProcessor.from_pretrained(processor_name)
Base model
openai/clip-vit-large-patch14