ModelScope

ModelScope

Alibaba Cloud
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About

MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components. Record and query experiments: code, data, config, and results. Package data science code in a format to reproduce runs on any platform. Deploy machine learning models in diverse serving environments. Store, annotate, discover, and manage models in a central repository. The MLflow Tracking component is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects.

About

This model is based on a multi-stage text-to-video generation diffusion model, which inputs a description text and returns a video that matches the text description. Only English input is supported. This model is based on a multi-stage text-to-video generation diffusion model, which inputs a description text and returns a video that matches the text description. Only English input is supported. The text-to-video generation diffusion model consists of three sub-networks: text feature extraction, text feature-to-video latent space diffusion model, and video latent space to video visual space. The overall model parameters are about 1.7 billion. Support English input. The diffusion model adopts the Unet3D structure, and realizes the function of video generation through the iterative denoising process from the pure Gaussian noise video.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Companies looking for an open source platform solution for the machine learning lifecycle

Audience

Users interested in an open source text-to-video AI video generation model

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

MLflow
Founded: 2018
United States
mlflow.org

Company Information

Alibaba Cloud
China
modelscope.cn/

Alternatives

Union Cloud

Union Cloud

Union.ai

Alternatives

Kaggle

Kaggle

Google
DVC

DVC

iterative.ai

Categories

Categories

Integrations

Apache Spark
Azure Machine Learning
Determined AI
HoneyHive
IBM watsonx.data integration
Keras
LLaMA-Factory
LiteLLM
Microsoft 365
OpenMetadata
Qwen
Qwen2.5
Qwen2.5-Coder
Qwen2.5-VL
Qwen3
Qwen3.6-27B
RapidSOS
Step 3.5 Flash
TensorFlow
Vectice

Integrations

Apache Spark
Azure Machine Learning
Determined AI
HoneyHive
IBM watsonx.data integration
Keras
LLaMA-Factory
LiteLLM
Microsoft 365
OpenMetadata
Qwen
Qwen2.5
Qwen2.5-Coder
Qwen2.5-VL
Qwen3
Qwen3.6-27B
RapidSOS
Step 3.5 Flash
TensorFlow
Vectice
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