This is a video action recognition model fine-tuned on the WLASL dataset based on the VideoMAE-Base architecture. After 200 epochs of training, it achieved a top-1 accuracy of 52.96% and a top-5 accuracy of 79.88% on the evaluation set, specifically designed for sign language action recognition tasks.

Computer VisionTransformers

A static quantized version of UME-R1-7B, supporting multiple tasks such as sentence similarity, embedding, zero-shot image classification, and video text-to-text. It offers various quantization types to meet different needs, from the lightweight Q2_K to the high-quality Q8_0 version.

MultimodalTransformersEnglish

Qwen3-VL is the most powerful vision-language model in the Tongyi series. It has excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, long context support, strong spatial and video dynamic understanding capabilities, and outstanding agent interaction capabilities.

MultimodalGguf

Qwen3-VL-32B-Thinking is the most powerful vision-language model in the Qwen series, with excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, long context processing, spatial and video dynamic understanding capabilities, and outstanding agent interaction capabilities.

MultimodalTransformers

Qwen3-VL-8B-Thinking is the most powerful vision-language model in the Tongyi Qianwen series. It has excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, long context support, strong spatial and video dynamic understanding capabilities, and outstanding agent interaction capabilities.

MultimodalGguf

Qwen3-VL is the most powerful vision - language model in the Tongyi series, with comprehensive upgrades in text understanding and generation, visual perception and reasoning, context length, spatial and video dynamic understanding, and agent interaction capabilities. This model offers both dense architecture and mixture - of - experts architecture, supporting flexible deployment from edge devices to the cloud.

MultimodalTransformers

Qwen3-VL is the most powerful vision-language model in the Qwen series, achieving comprehensive upgrades in all aspects, including excellent text understanding and generation capabilities, deeper visual perception and reasoning capabilities, longer context length, enhanced spatial and video dynamic understanding capabilities, and stronger agent interaction capabilities.

MultimodalTransformers

This model is a violence detection model based on the VideoMAE architecture. After pre-training on the Kinetics dataset, it was fine-tuned for 92 rounds for the violence detection task. The model uses the Vision Transformer architecture and is specifically designed for video content analysis, capable of identifying violent behaviors in videos.

Computer VisionTransformers

Qwen3-VL is the most powerful vision-language model in the Qwen series. It has excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, long context support, strong spatial and video dynamic understanding capabilities, and outstanding agent interaction capabilities. This version is a thinking-enhanced version with 2B parameters, specifically optimized for reasoning capabilities.

MultimodalTransformers

Qwen3-VL-30B-A3B-Thinking is the most powerful vision-language model in the Tongyi series. It has excellent text understanding and generation capabilities, in-depth visual perception and reasoning abilities, long context support, strong spatial and video dynamic understanding abilities, and agent interaction capabilities.

MultimodalGguf

Qwen3-VL is the most powerful vision-language model in the Tongyi series. It adopts a Mixture of Experts (MoE) architecture and provides weights in the GGUF format, supporting efficient inference on devices such as CPUs and GPUs. The model has been comprehensively upgraded in text understanding, visual perception, spatial understanding, video processing, etc.

MultimodalGguf

Qwen3-VL-30B-A3B-Instruct is the most powerful vision-language model in the Tongyi series. It adopts a mixture-of-experts model architecture and has excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities. It supports a 256K long context and video understanding, and can perform inference on a variety of devices.

MultimodalGguf

Qwen3-VL is the most powerful visual language model in the Tongyi series. It has excellent text understanding and generation capabilities, in - depth visual perception and reasoning abilities, long - context support, strong spatial and video dynamic understanding abilities, and agent interaction capabilities. This repository provides GGUF - format weights, supporting efficient inference on devices such as CPUs and GPUs.

MultimodalTransformers

Qwen3-VL-32B-Instruct is the most powerful vision-language model in the Tongyi series. It has excellent text understanding and generation capabilities, in-depth visual perception and reasoning abilities, long context support, strong spatial and video dynamic understanding abilities, and agent interaction capabilities.

MultimodalTransformers

Qwen3-VL-8B-Instruct is the most powerful visual language model in the Tongyi series, with excellent text understanding and generation capabilities, in-depth visual perception and reasoning abilities, long context support, and strong spatial and video dynamic understanding abilities.

MultimodalTransformers

Qwen3-VL-4B-Instruct is one of the most powerful vision-language models in the Tongyi series. It has been comprehensively upgraded in text understanding, visual perception, spatial understanding, video processing, etc. It supports running on a variety of hardware devices and has excellent multimodal reasoning capabilities.

MultimodalTransformers

Qwen3-VL-32B-Thinking is the most powerful vision-language model in the Qwen series. It has excellent text understanding and generation capabilities, in-depth visual perception and reasoning abilities, long context support, strong spatial and video dynamic understanding abilities, and outstanding agent interaction capabilities.

MultimodalTransformers

Qwen3-VL is the most powerful vision-language model in the Tongyi series, with excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, long context support, strong spatial and video dynamic understanding capabilities, and excellent agent interaction capabilities.

MultimodalTransformers

Qwen3-VL is the most powerful vision-language model in the Qwen series to date. It has been comprehensively upgraded in text understanding and generation, visual perception and reasoning, context length, spatial and video dynamic understanding, and agent interaction capabilities. This model adopts a Mixture of Experts (MoE) architecture, providing excellent multimodal processing capabilities.

MultimodalGguf

Qwen3-VL is the most powerful vision-language model in the Tongyi large model series. It has excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, long context support, strong spatial and video dynamic understanding capabilities, and outstanding intelligent agent interaction capabilities. This model uses a Mixture of Experts (MoE) architecture and is a thinking version for enhanced reasoning.

MultimodalGguf