Update autonlp-prodigy.md

autonlp-prodigy.md

@@ -94,7 +94,7 @@ Once you run the above command, you can go to the prodigy web interface (usually
 
 All you have to do is select which entity you want to label (PERSON, ORG, PRODUCT, LOCATION) and then select the text that belongs to the entity. Once you are done with one document, you can click on the green button and Prodigy will automatically provide you with next unlabelled document.
 
-![prodigy_ner_demo](assets/43_autonlp_prodigy/prodigy.png)
+![prodigy_ner_demo](assets/43_autonlp_prodigy/prodigy.gif)
 
 Using Prodigy, we started labelling the dataset. When we had around 20 samples, we trained a model using AutoNLP. Prodigy doesn't export the data in AutoNLP format, so we wrote a quick and dirty script to convert the data into AutoNLP format:
 
@@ -161,4 +161,4 @@ We believe with tools like AutoNLP and Prodigy it's very easy to create data and
 
 We have open-sourced the best model created using this process. You can try it [here](https://huggingface.co/abhishek/autonlp-prodigy-10-3362554). The labelled dataset can also be downloaded [here](https://huggingface.co/datasets/abhishek/autonlp-data-prodigy-10).
 
-Models are only state-of-the-art because of the data they are trained on.
+Models are only state-of-the-art because of the data they are trained on.