Hugging Face introduces NeoMME multilingual encoder
Hugging Face just launched NeoMME, a new model that handles both text and images across languages—no separate vision or text components required. The 260-million and 800-million parameter models use a single Transformer to process everything together, boosting speed and reducing storage needs. It can encode about 51 document pages per second and shrinks storage per page by over 99%. The model and checkpoints are now available for free reuse.
- Handles text and images with one Transformer model
- Available in 260M and 800M parameter sizes
- Encodes 51 pages per second on a single GPU
- Storage needed per page drops by over 99%
- Released openly under an Apache 2.0 license
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