Update README.md

README.md

@@ -5,6 +5,7 @@ widget:
 - text: "Text-to-image generation has traditionally focused on finding better modeling assumptions for training on a fixed dataset. These assumptions might involve complex architectures, auxiliary losses, or side information such as object part labels or segmentation masks supplied during training. We describe a simple approach for this task based on a transformer that autoregressively models the text and image tokens as a single stream of data. With sufficient data and scale, our approach is competitive with previous domain-specific models when evaluated in a zero-shot fashion."
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+[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AI-Growth-Lab/SciNerTopic/blob/main/notebooks/Sci_NERTopic.ipynb)
 
 NER model based on `allenai/scibert_scivocab_cased`
 Fine-tuned using the [SciERC Dataset](http://nlp.cs.washington.edu/sciIE/) to identify scientific terms:
@@ -30,7 +31,7 @@ E.g model, approach, prior knowledge, them, it...
 
 Check out how this model is used for NER-enhanced topic modelling.
 
-![https://colab.research.google.com/assets/colab-badge.svg](https://colab.research.google.com/github/AI-Growth-Lab/SciNerTopic/blob/main/notebooks/Sci_NERTopic.ipynb)
+[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/AI-Growth-Lab/SciNerTopic/blob/main/notebooks/Sci_NERTopic.ipynb)
 
 
 ## Use