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