Add More Model Comparisons

[shwetd19]

The current repository provides comparisons of various AI language models. However, there are several recent models and unique architectures that are not included in the existing comparisons. Expanding the dataset to include these models would enhance the repository's comprehensiveness and utility for users seeking to understand the landscape of AI language models.

Suggested Metrics for Comparison

• Performance Metrics: Accuracy, F1 score, perplexity, etc.
• Response Time: Average latency in generating responses.
• Training Data Size: Volume and diversity of training data used.
• Use Cases: Specific applications where each model excels (e.g., chatbots, summarization, translation).

Benefits

• Comprehensive Overview: Users will have access to a broader range of models, aiding in better decision-making for their specific needs.
• Up-to-Date Information: Incorporating newer models ensures that the repository remains relevant in a rapidly evolving field.
• Enhanced User Engagement: More options can lead to increased engagement from the community as they explore different models.

Additional Notes

Feel free to suggest any other models or metrics that could be included in this comparison. Collaboration is encouraged!

[Ahmet-Dedeler]

Hey,

If you can find the data for it this would be a great add.

The dataset I use only has the info I already have on the website, curious if there exists any other database we can combine to have a large one.

Let me know!

[shwetd19]

Hey @Ahmet-Dedeler ,

Thanks for the reply! I think adding models like Grok or Llama 3 could be cool—maybe even Mistral if we’re feeling adventurous. I’ll poke around Hugging Face and some papers to see if I can grab stats on accuracy, speed, and training data. No perfect database yet, but I’m down to piece it together.

How about I start with Grok and Llama 3 and share a quick sample? Let me know what you think!

Cheers!

[Ahmet-Dedeler]

Sounds great!