Update README.md

README.md

@@ -1,11 +1,10 @@
----
-license: apache-2.0
-language:
-- en
-pipeline_tag: image-to-image
-datasets:
-- ILSVRC/imagenet-1k
----
+---
+license: apache-2.0
+language:
+- en
+datasets:
+- ILSVRC/imagenet-1k
+---
 # Model Card for Model ID
 VIT-MAE-r is a fine-tuned version of MAE for image reconstuction. We release a version fine-tuned from [MAE-Large](https://huggingface.co/facebook/vit-mae-large)
 
@@ -17,8 +16,8 @@ VIT-MAE-r is already converted to hf format and should be able to be used direct
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [LM4LV: A Frozen Large Language Model for Low-level Vision Tasks](https://arxiv.org/abs/2405.15734v1)
+- **Repository:** [LM4LV](https://github.com/bytetriper/LM4LV)
+- **Paper:** [LM4LV: A Frozen Large Language Model for Low-level Vision Tasks](https://arxiv.org/abs/2405.15734v1)
 - **source model**: [MAE-Large](https://huggingface.co/facebook/vit-mae-large)
 
 ## How to Get Started with the Model
@@ -35,7 +34,7 @@ model = AutoModelForPreTraining.from_pretrained("bytetriper/vit-mae-r")
 
 This model achieves a rFID on ImageNet val set of 1.24, evaluated using the standard tensorflow tool provided by [Guided-Diffusion](https://github.com/openai/guided-diffusion/tree/main/evaluations)
 
-## Citation [optional]
+## Citation
 
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 
@@ -50,7 +49,7 @@ This model achieves a rFID on ImageNet val set of 1.24, evaluated using the stan
 
 
 
-## Model Card Authors [optional]
+## Model Card Authors
 
 Boyang Zheng