Update README.md

README.md

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   <img src="https://cdn-uploads.huggingface.co/production/uploads/650c7fbb8ffe1f53bdbe1aec/DTjDSq2yG-5Cqnk6giPFq.jpeg" width="50%" height="auto"/>
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-<p align='center', style='font-size: 16px;' >A Custom Model Enhanced for Educational Contexts: This specialized model integrates slide-text pairs from machine learning classes, leveraging a unique training approach. It connects a frozen pre-trained vision encoder (SigLip) with a frozen language model (Phi-2) through an innovative projector. The model employs attention mechanisms and language modeling loss to deeply understand and generate educational content, specifically tailored to the context of machine learning education. </p>
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-<p align='center' style='font-size: 16px;'>
-3B parameter model built by <a href="https://www.linkedin.com/in/manishkumarthota/">@Manish</a> using SigLIP, Phi-2, Language Modeling Loss, LLaVa data, and Custom setting training dataset.
-The model is released for research purposes only, commercial use is not allowed.
-</p>
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-Pretraining is done and if at all in future we are adding more question answer pairs, we can just do lora finetuning on top of this model
+<p align='center', style='font-size: 16px;' >A Custom 3B parameter Model Enhanced for Educational Contexts: This specialized model integrates slide-text pairs from machine learning classes, leveraging a unique training approach. It connects a frozen pre-trained vision encoder (SigLip) with a frozen language model (Phi-2) through an innovative projector. The model employs attention mechanisms and language modeling loss to deeply understand and generate educational content, specifically tailored to the context of machine learning education. Built by <a href="https://www.linkedin.com/in/manishkumarthota/">@Manish</a> The model is released for research purposes only, commercial use is not allowed. </p>
 
 ## How to use