阿里云百炼

• Multi-model support: provides the Qwen series (such as:Qwen3), third-party open-source and customized models, covering multiple modalities such as text, images, audio, and video.
• Model tuning and training: supports two methods, full-parameter training and efficient training. Users can upload datasets for labeling, filtering, and version management, and optimize model performance through Fine-tuning.
• Application building and orchestration: supports low-code and full-code development modes, provides functions such as Prompt optimization, knowledge base management, and function calling, and can quickly build agent applications and connect them to business processes.
• Application Square and plugin integration: provides a variety of preset application templates and rich plugins, supports flexible process orchestration, and meets the needs of different business scenarios.
• MCP service: connects intelligence, ready to use with one click, and supports exploring the full-cycle MCP services of Alibaba Cloud Model Studio.
• Data management and security: provides preprocessing tools such as data cleaning, labeling, and enhancement, and supports data encryption and permission management to ensure data security.
• Automated Machine Learning (AutoML): automatically completes data preprocessing, feature selection, model selection, and hyperparameter tuning, lowering the development threshold.
• Efficient deployment and cost control: supports one-click deployment and model version management, provides API and SDK integration, and charges on demand, reducing usage costs.
• One Key MCP : developers only need one Model Studio API Key to uniformly call the MCP services of 14 ecosystem partners, compatible with Qoder、Codex、Claude Code、Cursor and other mainstream Coding Agents.

How to use Alibaba Cloud Model Studio

• Registration and login: visit the Alibaba Cloud Model Studio official website, register an account, and log in.
• Quick experience: after logging in, click the homepage to enter the model experience page, and enter a question to get a model answer. After the experience ends, click the "Activate Model Calling" button and follow the prompts to complete service activation.
• Create an application: Click "Create Application" in "My Applications", and fill in basic information such as the application name and description. Select an appropriate model framework, such as Tongyi Qianwen, and start building the project. You can complete application building through low-code or full-code development modes, combined with features such as Prompt optimization and RAG (Retrieval-Augmented Generation).
• Model Invocation and Deployment: In the Model Square, select a model for operations such as experience, invocation, training, and deployment. Invoke models through API interfaces, supporting multiple languages such as Python and Node.js. Model Studio provides one-click deployment and MCP services that require no operations and maintenance. Based on the elastic resources of Function Compute, intelligent agents can be built quickly.
• Model Training and Optimization: When model performance does not meet requirements, model fine-tuning training can be performed. It provides features such as training data management and model fine-tuning, and dedicated models can be invoked through APIs.
• Application Publishing and Use: After completing application building, click "Publish Process" and go to "My Applications", where you can name and configure the application. The application can be integrated into other systems through APIs to implement more complex functions, such as converting the generated Markdown outline into a PPT.
• Resource Configuration and Cost Management: According to model training requirements, reasonably configure computing resources, including CPU and GPU types and quantities, as well as storage space. Model Studio provides flexible resource configuration solutions to ensure the optimal balance between training efficiency and cost.

Application Scenarios of Alibaba Cloud Model Studio

• Intelligent Customer Service: Based on the natural language processing capabilities of large models, enterprises can deploy intelligent customer service systems to automatically answer customer inquiries and provide personalized replies according to different business scenarios.
• Intelligent Marketing: Model Studio large models can help enterprises analyze consumer behavior, predict market trends, and generate personalized marketing content, such as promotional emails and advertising copy, improving the conversion rate and ROI of marketing campaigns.
• Content Generation and Creation: Model Studio large models can be used for content creation, such as writing news articles, generating creative copy, and writing technical documentation, greatly improving the efficiency and quality of content production.
• Intelligent Document Processing and Review: In fields such as law and finance, enterprises usually need to process large numbers of complex documents and contracts. Model Studio large models can help enterprises quickly extract key information, perform automated document classification, content review, and intelligent review, reducing human errors.
• Intelligent Recommendation System: Model Studio large models can analyze user behavior, text, and image data, and combine cross-modal learning capabilities to recommend more accurate content to users. For example, e-commerce platforms can use Model Studio large models to generate personalized product recommendations based on users' browsing history and purchase records, improving conversion rates.
• Medical Image Analysis and Diagnosis: In the medical field, the computer vision capabilities of Model Studio large models can help doctors analyze medical images and achieve automated disease screening and diagnostic assistance. By training on large amounts of medical image data, the model can quickly identify abnormalities and improve diagnostic efficiency and accuracy.