Update README.md

README.md

@@ -5,6 +5,8 @@ language:
 tags:
 - Autoregressive
 - Tokenizer
+base_model:
+- TencentARC/Open-MAGVIT2-Tokenizer-256-resolution
 ---
 
 ## Open-MAGVIT2: Democratizing Autoregressive Visual Generation
@@ -19,4 +21,4 @@ Until now, VQGAN, the initial tokenizer is still acting an indispensible role in
 
 Therefore, [MAGVIT2](https://arxiv.org/abs/2310.05737) proposes a powerful tokenizer for visual generation task, which introduces a novel LookUpFree technique when quantization and extends the size of codebook to $2^{18}$, exhibiting promising performance in both image and video generation tasks. And it plays an important role in the recent state-of-the-art AR video generation model [VideoPoet](https://arxiv.org/abs/2312.14125). However, we have no access to this strong tokenizer so far. ☹️
 
-In the codebase, we follow the significant insights of tokenizer design in MAGVIT-2 and re-implement it with Pytorch, achieving the closest results to the original so far. We hope that our effort can foster innovation, creativity within the field of Autoregressive Visual Generation. 😄
+In the codebase, we follow the significant insights of tokenizer design in MAGVIT-2 and re-implement it with Pytorch, achieving the closest results to the original so far. We hope that our effort can foster innovation, creativity within the field of Autoregressive Visual Generation. 😄