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README.md

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-license: mit
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+---
+license: mit
+---
+# PaliGemma-3B-MalayaLLM
+
+<img src="https://github.com/user-attachments/assets/8e8937a7-fd47-482c-acaf-48efc3c04597" alt="Baby MalayaLLM" width="300" height="auto">
+
+# Introducing the Developer:
+Discover the mind behind this model and stay updated on their contributions to the field
+https://www.linkedin.com/in/vishnu-prasad-j/
+
+# Model description
+This is a PaliGemma-3B based model for Malayalam captioning and Visual Question Answering.
+
+- **Model type:** A 3B PaliGemma-2 finetuned model on Malayalam captions and queries.
+- **Language(s):** Malayalam and English
+- **Datasets:**
+  * [VishnuPJ/SAM-LLAVA-20k-Malayalam-Caption-Pretrain](https://huggingface.co/datasets/VishnuPJ/SAM-LLAVA-20k-Malayalam-Caption-Pretrain)
+  * [VishnuPJ/laion-14k-GPT4V-LIVIS-Captions_Malayalam](https://huggingface.co/datasets/VishnuPJ/laion-14k-GPT4V-LIVIS-Captions_Malayalam)
+  * [VishnuPJ/Malayalam-VQA](https://huggingface.co/datasets/VishnuPJ/Malayalam-VQA)
+- **Caption Model-Full Precisoin:** [VishnuPJ/MalayaLLM-Paligemma-Caption-3B-Full-Precision](https://huggingface.co/VishnuPJ/MalayaLLM-Paligemma-Caption-3B-Full-Precision)
+- **Caption 4bit Quant:** [VishnuPJ/MalayaLLM-Paligemma-Caption-3B-4bitQuant](https://huggingface.co/VishnuPJ/MalayaLLM-Paligemma-Caption-3B-4bitQuant)
+- **VQA Model-Full Precison:** [VishnuPJ/MalayaLLM-Paligemma-VQA-3B-Full-Precision](https://huggingface.co/VishnuPJ/MalayaLLM-Paligemma-VQA-3B-Full-Precision)
+- **VQA 4bit Quant:** [VishnuPJ/MalayaLLM-Paligemma-VQA-3B-4bitQuant](https://huggingface.co/VishnuPJ/MalayaLLM-Paligemma-VQA-3B-4bitQuant)
+- **VQA LORA Adapters:** [VishnuPJ/MalayaLLM-Paligemma-VQA-3B-Adapters](https://huggingface.co/VishnuPJ/MalayaLLM-Paligemma-VQA-3B-Adapters)
+- **Training Precision:** `float16`,`4bit`
+
+# Dataset Creation
+I have used [indictrans2](https://huggingface.co/ai4bharat/indictrans2-en-indic-1B) for translating English datasets to Malayalam.
+
+# 🌟Happy coding💻🌟