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Average Ratings 0 Ratings

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ease
features
design
support

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Description

CogVideoX serves as a powerful tool for generating videos from text inputs. Prior to executing the model, it is essential to consult this guide to understand how we utilize the GLM-4 model for prompt optimization. This step is vital since the model performs best with extended prompts, and crafting an effective prompt has a significant impact on the quality of the resultant video. The guide includes both the inference code and the fine-tuning code for SAT weights, with recommendations to enhance it based on the framework of the CogVideoX model. Enterprising researchers leverage this code to advance their rapid development and stacking capabilities. In a captivating scene, a meticulously crafted wooden toy ship, featuring detailed masts and sails, sails gracefully over a soft, blue carpet designed to mimic the ocean's waves. The ship's hull boasts a deep brown hue adorned with tiny, intricate windows. The invitingly plush carpet serves as an ideal setting, evoking the vastness of the sea, while various toys and children's belongings scattered around further suggest a lively and imaginative atmosphere. This imaginative scenario not only showcases the capabilities of CogVideoX but also highlights the importance of a well-structured prompt in creating engaging visual narratives.

Description

This system utilizes a sophisticated multi-stage diffusion model for converting text descriptions into corresponding video content, exclusively processing input in English. The framework is composed of three interconnected sub-networks: one for extracting text features, another for transforming these features into a video latent space, and a final network that converts the latent representation into a visual video format. With approximately 1.7 billion parameters, this model is designed to harness the capabilities of the Unet3D architecture, enabling effective video generation through an iterative denoising method that begins with pure Gaussian noise. This innovative approach allows for the creation of dynamic video sequences that accurately reflect the narratives provided in the input descriptions.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

01.AI
CodeQwen
Qwen
Qwen-7B
Qwen2
Qwen2-VL
Qwen2.5
Qwen2.5-1M
Qwen2.5-Coder
Qwen2.5-Max
Qwen2.5-VL
Qwen3
Yi-Large

Integrations

01.AI
CodeQwen
Qwen
Qwen-7B
Qwen2
Qwen2-VL
Qwen2.5
Qwen2.5-1M
Qwen2.5-Coder
Qwen2.5-Max
Qwen2.5-VL
Qwen3
Yi-Large

Pricing Details

Free
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

CogVideoX

Website

github.com/THUDM/CogVideo

Vendor Details

Company Name

Alibaba Cloud

Country

China

Website

modelscope.cn/

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