A quantized version of LightOnOCR-1B-1025, specifically designed for image-to-text tasks and widely used in fields such as document understanding and visual language processing. This model supports multiple European languages and is suitable for scenarios such as OCR, PDF processing, and table recognition.

MultimodalGgufMultiple Languages

DeepSeek-OCR-8bit is an MLX format version converted from the DeepSeek-OCR model. It is a visual language model specifically optimized for Apple chips, supporting multilingual OCR recognition and image text understanding tasks.

MultimodalMlxOther

This is a multimodal model that supports multilingual processing, covering multiple fields such as natural language processing, code processing, and audio processing. It can perform various tasks such as automatic speech recognition, speech summarization, speech translation, and visual question answering.

MultimodalSafetensorsMultiple Languages

The Nanonets-OCR2-3B GGUF model is a powerful tool designed for document processing. It can intelligently convert various types of documents into structured Markdown format and has multiple advanced recognition and processing capabilities such as OCR, image-to-text conversion, PDF-to-Markdown conversion, and visual question answering.

MultimodalTransformersOther

DeepSeek-OCR is an advanced optical character recognition model developed by DeepSeek AI, focusing on exploring the boundaries of visual text compression and capable of efficiently extracting and converting text content from images.

MultimodalSafetensorsOther

This is a license plate detection model fine - tuned based on the DETR architecture and the DINOv3 visual backbone network. It achieved a loss value of 2.7008 on the evaluation set and is specifically designed for license plate recognition tasks.

Computer VisionTransformers

EraX-VL-7B-V1.5 is a powerful multimodal model specializing in Optical Character Recognition (OCR) and Visual Question Answering (VQA), excelling in multilingual environments with particular expertise in Vietnamese.

MultimodalTransformersMultiple Languages

Llama 3.2-Vision is a multimodal large language model developed by Meta, with image reasoning and text generation capabilities, supporting tasks such as visual recognition, image description, and question answering.

MultimodalTransformersMultiple Languages

AV-HuBERT is an audio-visual speech recognition model trained on the MuAViC multilingual audio-visual corpus, combining audio and visual modalities for robust performance.

MultimodalTransformers

An audio-visual speech recognition model trained on the MuAViC dataset, which combines audio and visual modalities to improve recognition performance in noisy environments.

MultimodalTransformers

Finedefics is an open-source multimodal large language model (MLLM) that enhances fine-grained visual recognition (FGVR) capabilities by incorporating object attribute descriptions.

MultimodalSafetensors

Llama 3.2-Vision is a multimodal large language model developed by Meta, supporting image and text inputs, optimized for visual recognition, image reasoning, and description tasks.

MultimodalTransformersMultiple Languages

Llama 3.2-Vision is a multimodal large language model developed by Meta, supporting both image and text inputs, capable of tasks such as visual recognition, image reasoning, and captioning.

MultimodalTransformersMultiple Languages

Llama 3.2-Vision is a multimodal large language model developed by Meta, supporting image and text input with text output, excelling in visual recognition, image reasoning, image captioning, and visual question answering tasks.

MultimodalTransformersMultiple Languages

Llama 3.2-Vision is a multimodal large language model series developed by Meta, supporting image+text input and text output, optimized for visual recognition, image reasoning, image captioning, and visual question answering tasks.

MultimodalTransformersMultiple Languages

Llama 3.2-Vision is a series of multimodal large language models developed by Meta, available in 11B and 90B scales, supporting image + text input and text output, optimized for visual recognition, image reasoning, image captioning, and visual question answering tasks.

MultimodalTransformersMultiple Languages

A multilingual audio-visual speech recognition model based on the MuAViC dataset, combining audio and visual modalities for robust performance

MultimodalTransformers

MiniCPM-V is a mobile GPT-4V-level multimodal large language model that supports single-image, multi-image, and video understanding, equipped with visual and optical character recognition capabilities.

MultimodalTransformersOther

GUIChat is a multimodal model based on Visual Question Answering (VQA), capable of understanding image content and answering related questions, specifically optimized for GUI element recognition and interaction.

MultimodalTransformers

A Japanese speech recognition model fine-tuned based on distil-whisper/distil-large-v2, specifically designed for Japanese audio transcription with optimizations for visual novel scenarios

Audio ProcessingTransformersMultiple Languages