Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models

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docarray Data structures multimodal cross-modal neural-search

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  • vision_transformer

    • We’re going to look at a model that Open AI has trained with a broad multilingual dataset: The xlm-roberta-base-ViT-B-32 CLIP model, which uses the ViT-B/32image encoder, and the XLM-RoBERTa multilingual language model. Both of these are pre-trained:

  • ImageNet21K

    Official Pytorch Implementation of: "ImageNet-21K Pretraining for the Masses"(NeurIPS, 2021) paper

    • ViT-B/32, using the ImageNet-21k dataset

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • Fashion12K_german_queries

    • We have collaborated with Toloka to curate a 12,000 item dataset of fashion images drawn from e-commerce websites, to which human annotators have added descriptive captions in German. Toloka has made the data available to the public on GitHub, but you can also download it from Jina directly in DocArray format by following the instructions in the next section.

  • fashion-200k

    Fashion 200K dataset used in paper "Automatic Spatially-aware Fashion Concept Discovery."

    • The images are a subset of the xthan/fashion-200k dataset, and we have commissioned their human annotations via Toloka’s crowdsourcing platform. Annotations were made in two steps. First, Toloka passed the 12,000 images to annotators in their large international user community, who added descriptive captions.

  • docarray

    Represent, send, store and search multimodal data

    • The German Fashion12k dataset is available for free use by the Jina AI community. After logging into Jina AI Cloud, you can download it directly in DocArrayformat:

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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