The PaliGemma 2 family consists of nine models with varying sizes and input resolutions, achieving state-of-the-art results in vision-language benchmarks like OCR, molecular recognition, and radiography report generation.
PaliGemma 2 leverages a pre-trained SigLIP-So400m image encoder alongside the Gemma 2 LLM, demonstrating significant advancements in generating factual image descriptions compared to existing VLMs.
Our team is eager to see how users interact with PaliGemma 2. The model's community engagement within the Gemmaverse is crucial for fostering innovation and collaborative projects.
With fine-tuned versions specifically designed for benchmark tasks, PaliGemma 2 is positioned to lead in various applications, including spatial reasoning and complex image captioning.
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