Explore Qwen2.5-VL 7B Instruct Model

Advanced multimodal model for text and image tasks.

Input: text · image Output: text Context: 32,768 tokens Release: 2024-08-28

Discover Qwen: Qwen2.5-VL 7B Instruct, a versatile multimodal model from Qwen, released in August 2024. This model features a substantial context window of 32,768 tokens, allowing it to handle complex inputs and outputs across both text and image modalities. With state-of-the-art visual understanding, it excels in tasks like video comprehension and multilingual text recognition. Whether you're looking to automate device operations or engage in high-quality video-based interactions, Qwen2.5-VL offers robust capabilities. It supports various parameters for customization, making it a flexible choice for diverse applications.

Use Cases

Here are a few ways teams apply Qwen: Qwen2.5-VL 7B Instruct in practice—from fast drafting to multimodal understanding. Adapt these ideas to your workflow.

Enhance video-based question answering

Automate device operations with visual inputs

Create multilingual content from images

Engage in complex reasoning tasks

Key Features

A quick look at the capabilities that make this model useful in real projects.

State-of-the-art visual understanding

Handles videos over 20 minutes

Integrates with devices for automation

Supports multiple languages

Large context window of 32,768 tokens

Specs

Overview

Vendor
qwen

Model ID
qwen/qwen-2.5-vl-7b-instruct

Release
2024-08-28

Modalities & context

Input
text · image

Output
text

Context
32,768 tokens

Parameters & defaults

Supported parameters: frequency_penalty, logit_bias, max_tokens, min_p, presence_penalty, repetition_penalty, seed, stop, temperature, top_k, top_p

Defaults: temperature 0.2, top_p 0.95

Benchmark tests: Qwen: Qwen2.5-VL 7B Instruct

We ran this model against a few representative prompts to show its range. Review the outputs below and be the judge.

Text

Prompt:

Write 150 words on how AI might positively upend work, leisure and creativity

The Qwen2.5-VL 7B Instruct model is a large language model designed for various natural language processing tasks. With 7 billion parameters, it is capable of understanding and generating human-like text, making it suitable for applications such as chatbots, content creation, and language translation. This model is particularly optimized for instruction-following tasks, allowing it to respond accurately to user prompts and queries. Typical use cases include customer support automation, educational tools, and interactive applications where user engagement is essential. However, users should be aware of certain constraints, such as the potential for generating incorrect or nonsensical information, and the need for careful oversight in sensitive applications. Additionally, the model's performance may vary based on the complexity of the input and the specificity of the instructions provided.

Run this prompt on Upend.AI

Image

Prompt:

Generate an SVG of a pelican riding a bicycle.

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up.end

/ˌəpˈend/

verb

To “upend” means to completely disrupt, overturn, or drastically change the established order or structure of something. It implies a significant shift or alteration that can potentially have far-reaching consequences. When something is upended, it is turned upside down or transformed in a way that challenges conventional norms or expectations. The term often carries a sense of innovation, transformation, and sometimes even a hint of upheaval, indicating that the changes are not just minor adjustments but rather a fundamental reimagining of the status quo.

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