Update README.md

README.md

@@ -40,7 +40,7 @@ license: apache-2.0
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 > For visual generation, discrete autoregressive models often struggle with poor tokenizer reconstruction, difficulties in sampling from large vocabularies, and slow token-by-token generation speeds. We present **BitDance**, which addresses these challenges via a large-vocabulary binary tokenizer, a binary diffusion head for sampling in large discrete space, and a next-patch diffusion paradigm that enables efficient multitoken prediction. BitDance is an open-source discrete autoregressive foundation model with 14B parameters, trained on large-scale multimodal tokens. While maintaining the standard language modeling paradigm for text tokens, BitDance employs a next-patch diffusion paradigm for visual tokens to predict multiple tokens in parallel—up to 64 per step. This unified multimodal framework is simple, scalable, and capable of efficiently generating high-resolution, photorealistic images.
 
-This repository hosts the BitDance model weights for ImageNet Generation. For detailed instructions, please visit our [GitHub Repository](https://github.com/shallowdream204/BitDance).
+This repository hosts the **BitDance** model weights for ImageNet Generation. For detailed instructions, please visit our [GitHub Repository](https://github.com/shallowdream204/BitDance).
 
 
 ## 🪪 License