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Amadou Cisse
Amadou98
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Amadou98/crossner-extractor-comparison
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Amadou98/crossner-extractor-comparison
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π₯ New multimodal leaderboard on the hub: ConTextual! Many situations require models to parse images containing text: maps, web pages, real world pictures, memes, ... πΌοΈ So how do you evaluate performance on this task? The ConTextual team introduced a brand new dataset of instructions and images, to test LMM (large multimodal models) reasoning capabilities, and an associated leaderboard (with a private test set). This is super exciting imo because it has the potential to be a good benchmark both for multimodal models and for assistants' vision capabilities, thanks to the instructions in the dataset. Congrats to @rohan598, @hbXNov, @kaiweichang and @violetpeng !! Learn more in the blog: https://huggingface.co/blog/leaderboard-contextual Leaderboard: https://huggingface.co/spaces/ucla-contextual/contextual_leaderboard
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CrossNER extractor comparison
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Compare NER models across multiple domains
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