Social media platforms have become integral to our daily lives, facilitating instant sharing of thoughts and ideas. While these platforms often host inspiring, motivational, and positive content, the research community has recognized the significance of such messages by labeling them as “hope speech”. In light of this, we delve into the detection of hope speech on social media platforms. Specifically, we explore various transformer-based model setups for the LT-EDI shared task at RANLP 2023. We observe that the performance of the models varies across languages. Overall, the finetuned m-BERT model showcases the best performance among all the models across languages. Our models secured the first position in Bulgarian and Hindi languages and achieved the third position for the Spanish language in the respective task.