Update README.md

README.md

@@ -6,11 +6,11 @@ pipeline_tag: zero-shot-image-classification
 ---
 
 ## CLIP-ViT-H-14-laion2B-2bit_g16_s128-HQQ
-This is a version of the ViT-H-14 model based on timm's ```vit_huge_patch14_clip_224.laion2b``` quantized to 2-bit via Half-Quadratic Quantization (HQQ): https://mobiusml.github.io/hqq/
+This is a version of the ViT-H-14 model based on timm's ```vit_huge_patch14_clip_224.laion2b``` quantized to 2-bit via Half-Quadratic Quantization (HQQ): https://mobiusml.github.io/hqq_blog/
 
 This 2-bit model achieves a 0.716 zero-shot top-1 accuracy on Imagenet, outperforming a full-precision ViT-B-32 (0.664).
 
-To run the model, install the HQQ library from https://github.com/mobiusml/hqq/tree/main/code and use it as follows:
+To run the model, install the HQQ library from https://github.com/mobiusml/hqq and use it as follows:
 ``` Python
 from hqq.models.vit import ViTHQQ
 model = ViTHQQ.from_quantized("mobiuslabsgmbh/CLIP-ViT-H-14-laion2B-2bit_g16_s128-HQQ")