23건 · 관련도순
Build image captioning, visual question answering, and text-based image search with BLIP-2. The skill explains model selection, batch processing, and memory-saving settings, with Python examples for connecting image understanding to language models.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Build image captioning, visual question answering, and text-based image search with BLIP-2. The skill guides model selection, batch processing, and memory optimization, with examples for understanding images without training for each specific task.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Build image-based conversations with LLaVA, an AI model that combines image understanding with language. Covers setup, model selection, image descriptions, follow-up questions, and memory-saving options for running models on a GPU.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Build image classification and search workflows by comparing images with text descriptions. Covers classification without additional training, similarity scoring, batch processing, and storing image representations in a vector database for retrieval.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Guides image classification and search with OpenAI's CLIP by comparing images with text descriptions, without additional training. Includes batch processing, image-text matching, and category-based checks for potentially inappropriate images.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Build image conversations with LLaVA, a model that connects image recognition with language. This skill guides setup, image descriptions, visual questions, and follow-up conversations, with examples for Python, command-line use, and a Gradio interface.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Framework de pré-treinamento visão-linguagem que conecta codificadores de imagem congelados e LLMs. Use quando você precisar de legendagem de imagens, resposta a perguntas visuais, recuperação imagem-texto ou chat multimodal com desempenho zero-shot de última geração.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use LLaVA, a model that understands images and text, to answer questions about pictures, write image descriptions, and build image chat applications. Includes guidance for setup, ongoing conversations, and model memory options.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Configure supervised fine-tuning for models that process images and text. Define which components remain unchanged, set LoRA adapters for updating selected model weights, choose image resolution limits, and investigate training runs whose evaluation results fail to improve.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Use Dexbotic to prepare DexData, train and serve vision-language-action policies, evaluate checkpoints, and integrate explicitly external RL or robot backends.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Builds ML pipelines: EDA, features, leakage checks, evaluation. Use when doing data science or explaining fairness, privacy, speech, vision-language, or diffusion mechanics.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
OCRs scanned or image-only corpora with vision-language models in four phases. Triage inventories the scans, identifies script and language, and shortlists models by script, hardware, and data constraints. Evaluate selects a system by measured CER or WER against ground truth, using born-digital twins, a second reader, and decision rules set in advance. Run builds the production pipeline. Clean removes model artifacts, audits what every cleaning rule deletes, corrects with rule-based and LLM passes, and records provenance. Use when choosing an OCR model for a corpus, measuring OCR accuracy, transcribing scans at scale, or correcting raw OCR. Born-digital documents with text layers go to doc-to-markdown; runs on Leiden's ALICE cluster add vlm-ocr-alice.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
OCR scanned or image-only corpora with vision-language models in four phases: `triage` inventories the scans, identifies script and language, and shortlists models by script, hardware, and data constraints; `evaluate` picks a system by measured CER/WER against ground truth, using born-digital twins, a second reader, and decision rules set in advance; `run` builds the production pipeline; and `clean` removes model artifacts, audits what every cleaning rule deletes, corrects with rule-based and LLM passes, and records provenance. Born-digital documents with a text layer go to $doc-to-markdown; runs on Leiden's ALICE cluster add $vlm-ocr-alice.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Local vision-language model for image analysis using SmolVLM-2B
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Semantic image-text matching with CLIP and alternatives. Use for image search, zero-shot classification, similarity matching. NOT for counting objects, fine-grained classification (celebrities, car models), spatial reasoning, or compositional queries. Activate on "CLIP", "embeddings", "image similarity", "semantic search", "zero-shot classification", "image-text matching".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Assistente de Linguagem Grande e Visão. Habilita ajuste de instrução visual e conversas baseadas em imagem. Combina encoder de visão CLIP com modelos de linguagem Vicuna/LLaMA. Suporta chat multi-turno com imagem, resposta a perguntas visuais e seguimento de instruções. Use para chatbots visão-linguagem ou tarefas de compreensão de imagem. Melhor para análise conversacional de imagem.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Modelo da OpenAI que conecta visão e linguagem. Permite classificação de imagens com zero-shot, correspondência imagem-texto e recuperação cross-modal. Treinado em 400M pares imagem-texto. Use para busca de imagens, moderação de conteúdo ou tarefas visão-linguagem sem fine-tuning. Melhor para compreensão geral de imagens.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Semantic image-text matching with CLIP and alternatives. Use for image search, zero-shot classification, similarity matching. NOT for counting objects, fine-grained classification (celebrities, car models), spatial reasoning, or compositional queries. Activate on "CLIP", "embeddings", "image similarity", "semantic search", "zero-shot classification", "image-text matching".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.