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InnovatorLab/Innovator-VL-Instruct-46M

Innovator-VL-Instruct-46M Paper | Code 🤗🤗 The data is being uploaded continuously Introduction To further enhance the model’s ability to handle a broad range of visual tasks with accurate, grounded, and instruction-aligned responses, we perform full-parameter visual instruction supervised fine-tuning (SFT).This SFT stage serves as a critical bridge between multimodal pretraining and subsequent reinforcement learning, providing both general capability coverage and a… See the full description on the dataset page: https://huggingface.co/datasets/InnovatorLab/Innovator-VL-Instruct-46M.

Author / organizationInnovatorLab
License (as declared)mit
Downloads66.9K (as reported by Hugging Face)
Likes12
Created24 January 2026
Last updated at source12 February 2026
multimodalvision-languagevisual-instruction-tuningsupervised-fine-tuningsftinstruction-followingchain-of-thoughtmulti-step-reasoningscientific-reasoningscience
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