Update README.md

README.md

@@ -13,8 +13,8 @@ This 2-bit model achieves a 0.716 zero-shot top-1 accuracy on Imagenet, outperfo
 ### Basic Usage
 To run the model, install the HQQ library from https://github.com/mobiusml/hqq and use it as follows:
 ``` Python
-from hqq.models.vit_timm import ViTHQQ
-model = ViTHQQ.from_quantized("mobiuslabsgmbh/CLIP-ViT-H-14-laion2B-2bit_g16_s128-HQQ")
+from hqq.engine.timm import HQQtimm
+model = HQQtimm.from_quantized("mobiuslabsgmbh/CLIP-ViT-H-14-laion2B-2bit_g16_s128-HQQ")
 ```
 
 ### Zero-Shot Classification
@@ -31,8 +31,8 @@ orig_model, _ , preprocess = open_clip.create_model_and_transforms('ViT-H-14', p
 tokenizer  = open_clip.get_tokenizer('ViT-H-14')
 model_text = orig_model.encode_text
 
-from hqq.models.vit_timm import ViTHQQ
-model_visual = ViTHQQ.from_quantized("mobiuslabsgmbh/CLIP-ViT-H-14-laion2B-2bit_g16_s128-HQQ")
+from hqq.engine.timm import HQQtimm
+model = HQQtimm.from_quantized("mobiuslabsgmbh/CLIP-ViT-H-14-laion2B-2bit_g16_s128-HQQ")
 
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