somosnlp
/

NoticIA-7B

@@ -61,7 +61,7 @@ widget:
 We define a clickbait article as one that seeks to attract the reader's attention through curiosity. To do this, the headline poses a question or an incomplete, sensationalist, exaggerated, or misleading statement. The answer to the question generated by the headline usually does not appear until the end of the article, which is preceded by a large amount of irrelevant content. The goal is for the user to enter the website through the headline and then scroll to the end of the article, viewing as much advertising as possible. Clickbait articles tend to be of low quality and do not provide value to the reader beyond the initial curiosity. This phenomenon undermines public trust in news sources and negatively affects the advertising revenues of legitimate content creators, who could see their web traffic reduced.
-We present a 7B parameter model, trained with the dataset [NoticIA](https://huggingface.co/datasets/somosnlp/NoticIA-it). This model is capable of generating concise and high-quality summaries of articles with clickbait headlines.
 - **Developed by:** [Iker García-Ferrero](https://ikergarcia1996.github.io/Iker-Garcia-Ferrero/), [Begoña Altuna](https://www.linkedin.com/in/bego%C3%B1a-altuna-78014139)
 - **Funded by:** SomosNLP, HuggingFace, [HiTZ Zentroa](https://www.hitz.eus/)
@@ -275,7 +275,7 @@ The exact training configuration is available at: https://huggingface.co/somosnl
 #### Testing Data
-We use the Test split of the NoticIA dataset: https://huggingface.co/datasets/somosnlp/NoticIA-it
 #### Prompts
@@ -321,7 +321,7 @@ We conducted all our experiments on a machine equipped with four NVIDIA A100 GPU
 - Deepspeed: https://github.com/microsoft/DeepSpeed
 - Pytorch: https://pytorch.org/
-Our code is available at: [https://github.com/ikergarcia1996/NoticIA](https://github.com/ikergarcia1996/NoticIA)
 ## License

 We define a clickbait article as one that seeks to attract the reader's attention through curiosity. To do this, the headline poses a question or an incomplete, sensationalist, exaggerated, or misleading statement. The answer to the question generated by the headline usually does not appear until the end of the article, which is preceded by a large amount of irrelevant content. The goal is for the user to enter the website through the headline and then scroll to the end of the article, viewing as much advertising as possible. Clickbait articles tend to be of low quality and do not provide value to the reader beyond the initial curiosity. This phenomenon undermines public trust in news sources and negatively affects the advertising revenues of legitimate content creators, who could see their web traffic reduced.
+We present a 7B parameter model, trained with the dataset [NoticIA-it](https://huggingface.co/datasets/somosnlp/NoticIA-it). This model is capable of generating concise and high-quality summaries of articles with clickbait headlines.
 - **Developed by:** [Iker García-Ferrero](https://ikergarcia1996.github.io/Iker-Garcia-Ferrero/), [Begoña Altuna](https://www.linkedin.com/in/bego%C3%B1a-altuna-78014139)
 - **Funded by:** SomosNLP, HuggingFace, [HiTZ Zentroa](https://www.hitz.eus/)
 #### Testing Data
+We use the Test split of the NoticIA-it dataset: https://huggingface.co/datasets/somosnlp/NoticIA-it
 #### Prompts
 - Deepspeed: https://github.com/microsoft/DeepSpeed
 - Pytorch: https://pytorch.org/
+Our code is available at [https://github.com/ikergarcia1996/NoticIA](https://github.com/ikergarcia1996/NoticIA)
 ## License