In this article, we build a simple video summarizer application using Qwen2.5-Omni 3B model with the UI powered by Gradio. The post Video Summarizer Using Qwen2.5-Omni appeared first on DebuggerCafe.| DebuggerCafe
In this article, we cover the introduction to BAGEL, an unified multimodal model for image generation, image editing, and free-form image manipulation with non-thinking and thinking capabilties. The post Introduction to BAGEL: An Unified Multimodal Model appeared first on DebuggerCafe.| DebuggerCafe
Qwen2.5-Omni is a multimodal generative AI model capable of accepting text, image, audio, and video as input while outputting text and audio.| DebuggerCafe
Qwen2.5-VL is the newest member in the Qwen Vision Language family, capable of image captioning, video captioning, and object detection.| DebuggerCafe
Phi-4 Mini and Phi-4 Multimodal are the latest Small Language Models for Chatting and Multimodal instruction following by Microsoft.| DebuggerCafe
Qwen2 VL is a Vision Language model with the Qwen2 Language Decoder and Vision Transformer model from DFN as the image encoder.| DebuggerCafe
Fine-tuning Llama 3.2 Vision on a LaTeX2OCR dataset to predict raw LaTeX equations from images and creating a Gradio application.| DebuggerCafe
Llama 3.2 Vision model is a multimodal VLM from Meta belonging to the Llama 3 family that brings the capability to feed images to the model.| DebuggerCafe