UForm v2 – tiny CLIP-like embeddings in 21 languages and Graphcore API
I want to share the most recent model release we have prepared. It's a Vision-Language understanding Transformer. It has 40% fewer parameters than vanilla CLIP while performing much better on text-to-image retrieval, where it's also beneficial that our output embeddings have 2x fewer dimensions (256 vs. 512). Moreover, it supports 21 languages, including popular English, Hindi, Chinese, Arabic, and lower-resource languages like Ukrainian, Hebrew, and Armenian. We have packed the library into ONNX and CoreML, providing PyTorch inference code for CPUs and GPUs and PopTorch code for Graphcore…
In plain words
UForm v2 is a Vision-Language Transformer model for understanding images and text that uses 40% fewer parameters than CLIP while achieving better text-to-image retrieval performance. The model supports 21 languages ranging from major ones like English and Chinese to lower-resource languages like Ukrainian and Armenian. It generates compact 256-dimensional embeddings instead of 512, reducing memory requirements. The library includes implementations for PyTorch on CPUs and GPUs, ONNX, CoreML, and PopTorch for Graphcore IPU hardware, making it accessible for developers building multilingual vision-language applications.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
I want to share the most recent model release we have prepared. It's a Vision-Language understanding Transformer. It has 40% fewer parameters than vanilla CLIP while performing much better on text-to-image retrieval, where it's also beneficial that our output embeddings have 2x fewer dimensions (256 vs. 512). Moreover, it supports 21 languages, including popular English, Hindi, Chinese, Arabic, and lower-resource languages like Ukrainian, Hebrew, and Armenian. We have packed the library into ONNX and CoreML, providing PyTorch inference code for CPUs and GPUs and PopTorch code for Graphcore IPUs. Demo: http://usearch-images.com/ Blog: https://www.unum.cloud/blog/2023-08-17-uform-graphcore Looking forward to your feedback!
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