Fix typos

app.py

@@ -140,31 +140,34 @@ st.info("I crafted this dataset using a more powerful LLM and scripts, no need f
 `https://huggingface.co/datasets/wgcv/website-title-description`
 
 # Models
-My objective was to show that it was possible to create a small ML model from a bigger LLM model that could achieve good or better results in specific tasks compared to the original LLM
+The objective of the project was to show that it was possible to create a small ML model from a bigger LLM model that could achieve good or better results in specific tasks compared to the original LLM
 
 Given the substantial volume of data, training a model from scratch was deemed impractical. Instead, our approach focused on evaluating the performance of existing pre-trained models as a baseline. This strategy served as an optimal starting point for developing a custom, lightweight model tailored to our specific use case: enhancing browser tab organization and efficiently summarizing the core concepts of favorited websites.
 
 ### T5-small
-- The [T5-small](https://huggingface.co/wgcv/tidy-tab-model-t5-small) model is a finetuning of google-t5/t5-small.
-- It's a text-to-text model
-- It's a general model for all NLP tasks
-- The task is defined by the input format
-- To perform summarization, prefix the text with 'summarize:'
-- 60.5M parameters
-- Disclaimer: I retrained the model once more because I observed poor results.
+- The [T5-small](https://huggingface.co/wgcv/tidy-tab-model-t5-small) model is a fine-tuned of google-t5/t5-small.
+- It's a text-to-text model.
+- It's a general model for all NLP tasks.
+- The task is defined by the input format.
+- To perform summarization, prefix the text with 'summarize:'.
+- 60.5M parameters.
+- Disclaimer: The model was retrained once more because poor inference was observed.
+
+
+
 
 ### Pegasus-xsum
-- The [Pegasus-xsum](https://huggingface.co/wgcv/tidy-tab-model-pegasus-xsum) model is a finetuning of google/pegasus-xsum.
-- It's a text-to-text model
-- It's a specialized summarization model
-- 570M params
+- The [Pegasus-xsum](https://huggingface.co/wgcv/tidy-tab-model-pegasus-xsum) model is a fine-tuned of google/pegasus-xsum.
+- It's a text-to-text model.
+- It's a specialized summarization model.
+- 570M params.
 
 ### Bart-large
-- The [Bart-large](https://huggingface.co/wgcv/tidy-tab-model-bart-large-cnn) model is a finetuning of facebook/bart-large-cnn.
+- The [Bart-large](https://huggingface.co/wgcv/tidy-tab-model-bart-large-cnn) model is a fine-tuned of facebook/bart-large-cnn.
 - Prior to our fine-tuning, it was fine-tuned on the CNN/Daily Mail dataset.
 - It's a BART model, using a transformer encoder-decoder (seq2seq) architecture.
 - BART models typically perform better with small datasets compared to text-to-text models.
-- 406M params
+- 406M params.