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MangaliCa is the first publicly available Hungarian–English bilingual vision–language model designed for image captioning and image–text retrieval. The model is built on the CoCa (Contrastive Captioner) framework and...
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MangaliCa is the first publicly available Hungarian–English bilingual vision–language model designed for image captioning and image–text retrieval. The model is built on the CoCa (Contrastive Captioner) framework and...
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1 QuelleVerifiziert 17. Sept.
Modellartefakte
64 Artefaktecheckpoints/checkpoint-100352-gbc/model.safetensors
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Herunterladen--- language: - en - hu license: cc-by-nc-sa-4.0 tags: - vision-language - image-captioning - image-text-retrieval - multilingual datasets: - Obscure-Entropy/MangaliCa_EN-HU metrics: - recall@k - mrr - ndcg pipeline_tag: image-to-text library_name: transformers model-index: - name: MangaliCa results: - task: type: image-text-retrieval dataset: type: image-text name: GBC-10M metrics: - name: R@1 type: R@1 value: 0.356 verified: false - task: type: image-text-retrieval dataset: type: image-text name: MS-COCO metrics: - name: R@1 type: R@1 value: 0.060 verified: false - task: type: image-text-retrieval dataset: type: image-text name: text-to-image-2M metrics: - name: R@1 type: R@1 value: 0.415 verified: false - task: type: image-text-retrieval dataset: type: image-text name: XM3600 metrics: - name: R@1 type: R@1 value: 0.113 verified: false --- # 🐗 MangaliCa: A Bilingual Vision–Language Model for Hungarian–English Image Captioning and Retrieval <div align="center"> <img src="./assets/mangalica.jpg" width="50%" /> </div> ## Model Description **MangaliCa** is the first publicly available Hungarian–English bilingual vision–language model designed for image captioning and image–text retrieval. The model is built on the CoCa (Contrastive Captioner) framework and jointly optimizes contrastive alignment and autoregressive caption generation across two languages. MangaliCa integrates: - CLIP ViT-L/14 as a frozen vision encoder - TinyLlama 1.1B as a text decoder, extended with cross-attention - Language-conditioning tokens for explicit bilingual control - LoRA adapters for memory-efficient fine-tuning > [!CAUTION] > The model was trained on a newly constructed **70M-sample Hungarian–English bilingual image–caption dataset**, the largest multimodal dataset involving Hungarian to date. --- ## Intended Uses ### Supported Tasks - **Image captioning** (Hungarian and English) - **Image–text retrieval** (text-to-image, image-to-text) - **Cross-lingual text–text retrieval** - Multimodal embedding extraction for RAG or search systems ### Example Use Cases - Hungarian-language multimodal assistants - Bilingual image search engines - Vision-enabled Retrieval-Augmented Generation (RAG) - Research on medium-resource multilingual vision–language learning --- ## 🪛 Model Architecture - **Vision Encoder**: CLIP ViT-L/14 (frozen,...
Source context: 0 downloads · 0 likes · Pipeline image-to-text · Library transformers · Repo Obscure-Entropy/MangaliCa
