Results for “image-text-retrieval”

OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.

OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.

OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.

Retrieve relevant information from a knowledge base using semantic, keyword, or hybrid search to ground a query. Use when the task starts with a corpus or index that must be searched; use context-ranking when candidate chunks already exist and only need ordering.

Explains dense vector embeddings, their key concepts, common use cases, and best practices for semantic search and RAG applications.

SynthText: Synthetic Data for Text Detection

Index folders of PDFs and other documents into LanceDB for vector search, then query them with semantic search, page filters, verbatim quotes, and cross-document aggregation.

OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.

Search GIF providers with CLI/TUI, download results, and extract stills/sheets.

DALL-E: Zero-Shot Text-to-Image Generation

TextVQA: Towards Reasoning about Text in Images

Search GIF providers with CLI/TUI, download results, and extract stills/sheets.

Search GIF providers with CLI/TUI, download results, and extract stills/sheets.

DashScope (Alibaba Cloud Bailian / 阿里云百炼) integration — image generation (qwen-image-2.0-pro), text-to-speech (qwen3-tts-flash), and ASR with word-level timestamps (qwen3-asr-flash-filetrans). Use when generating images via Qwen-Image, narrating via Qwen-TTS, or transcribing with word-level timestamps via Qwen-ASR.

Flamingo: A Visual Language Model for Few-Shot Learning

Extract text from PDFs/scans (pymupdf, marker-pdf).

Extracts text from PDFs and scanned documents, choosing the cheapest method that works, from direct file reads to full OCR.

Search GIF providers with CLI/TUI, download results, and extract stills/sheets.

CapsFusion: Rethinking Image-Text Data at Scale

Extracts structured image metadata from Google Images via the BrowserAct API, including thumbnails, titles, source logos, and click-through URLs.

Generate images using Google Gemini 3.1 Flash Image Preview via the inference.sh CLI, with support for text-to-image, image editing, multi-image input, and Google Search grounding.

Build and debug Retrieval-Augmented Generation pipelines — chunking, embedding, retrieval, reranking

Generates images and text via reverse-engineered Gemini Web API, supporting reference images and multi-turn conversations.

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas.

Search meme templates, suggest formats, and generate local or hosted image memes.

OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.

Upscale and enhance images using Real-ESRGAN, Thera, FLUX Upscaler, and Topaz via the inference.sh CLI.

Sigmoid Loss for Language Image Pre-Training

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Image Seo — Skill especializada para otimizar imagens para mecanismos de busca, melhorando a visibilidade e performance.