Add static rendering of tables.

introduction.md

@@ -193,6 +193,8 @@ described by the original caption. As evaluation metrics we use the MRR@K.
 | MRR@5           | **0.5039**   | 0.3957|
 | MRR@10          | **0.5204**   | 0.4129|
 
+_If the table above doesn not show, you can have a look at it [here](https://huggingface.co/spaces/clip-italian/clip-italian-demo/raw/main/static/img/table_imagenet.png)._
+
 It is true that we used the training set of MSCOCO-IT in training, and this might give us an advantage. However, the original CLIP model was trained
 on 400million images (and some of them might have been from MSCOCO).
 
@@ -209,6 +211,8 @@ We evaluate the models computing the accuracy at different levels.
 | Accuracy@10     |  **52.55**   | 42.91 |
 | Accuracy@100    |  **81.08**   | 67.11 |
 
+_If the table above doesn not show, you can have a look at it [here](https://huggingface.co/spaces/clip-italian/clip-italian-demo/raw/main/static/img/table_IR.png)._
+
 ### Discussion
 
 Our results confirm that CLIP-Italian is very competitive and beats mCLIP on the two different task