Update README.md

README.md

@@ -62,14 +62,17 @@ Model Selection and Evaluation:
 - Understand the strengths and limitations of each model in different conversational contexts.
 
 Fine-tuning:
- - speed, translations were truncated so we needed to split the amount of text, only certain languages were available 
+- Address issues such as speed and translation accuracy by fine-tuning model parameters and configurations.
+- Implement strategies to mitigate challenges such as text truncation and limited language support to enhance overall user experience.
+- Iterate on model architecture, hyperparameters, and data preprocessing techniques to achieve desired outcomes and user satisfaction.
 
 Hugging Face:
-- have to have a requirements doc
-- must be py not our jupiter
+- Emphasize the necessity of creating a comprehensive requirements document outlining dependencies, libraries, and configurations required for Hugging Face model integration.
+- Avoid reliance on Jupyter notebooks for production-level deployment due to limitations in scalability, version control, and reproducibility.
 
-Streamlit VS Gradio
- - heheh
+Streamlit VS Gradio:
+- Recognized Streamlit's appeal for deployment purposes, particularly for its visually appealing characteristics and user interface elements.
+- However, prioritized Gradio for deployment due to its compatibility with the core functionality and focus of our model, prioritizing model performance and functionality over visualization aesthetics.
 
 
 ## Opportunities and Next Steps