ChenRocks/UNITER
A multimodal foundation model that learns joint image-text representations by pre-training on large-scale image-caption pairs.
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UNITER is a transformer-based vision-language model that learns unified representations by jointly encoding images and text. The model is pre-trained on four types of tasks: masked language modeling, masked region modeling, image-text matching, and word-region alignment. Released checkpoints include UNITER-base and UNITER-large, with support for fine-tuning on NLVR2, VQA, VCR, SNLI-VE, image-caption retrieval, and referring expression comprehension tasks.
Frequently asked
- What is ChenRocks/UNITER?
- A multimodal foundation model that learns joint image-text representations by pre-training on large-scale image-caption pairs.
- Is UNITER open source?
- Yes — ChenRocks/UNITER is an open-source project tracked on heatdrop.
- What language is UNITER written in?
- ChenRocks/UNITER is primarily written in Python.
- How popular is UNITER?
- ChenRocks/UNITER has 799 stars on GitHub.
- Where can I find UNITER?
- ChenRocks/UNITER is on GitHub at https://github.com/ChenRocks/UNITER.