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Description
Utilize sophisticated coding and language models across a diverse range of applications.
Harness the power of expansive generative AI models that possess an intricate grasp of both language and code, paving the way for enhanced reasoning and comprehension skills essential for developing innovative applications. These advanced models can be applied to multiple scenarios, including writing support, automatic code creation, and data reasoning. Moreover, ensure responsible AI practices by implementing measures to detect and mitigate potential misuse, all while benefiting from enterprise-level security features offered by Azure.
With access to generative models pretrained on vast datasets comprising trillions of words, you can explore new possibilities in language processing, code analysis, reasoning, inferencing, and comprehension.
Further personalize these generative models by using labeled datasets tailored to your unique needs through an easy-to-use REST API. Additionally, you can optimize your model's performance by fine-tuning hyperparameters for improved output accuracy. The few-shot learning functionality allows you to provide sample inputs to the API, resulting in more pertinent and context-aware outcomes. This flexibility enhances your ability to meet specific application demands effectively.
Description
Qwen LLM represents a collection of advanced large language models created by Alibaba Cloud's Damo Academy. These models leverage an extensive dataset comprising text and code, enabling them to produce human-like text, facilitate language translation, craft various forms of creative content, and provide informative answers to queries.
Key attributes of Qwen LLMs include:
A range of sizes: The Qwen series features models with parameters varying from 1.8 billion to 72 billion, catering to diverse performance requirements and applications.
Open source availability: Certain versions of Qwen are open-source, allowing users to access and modify the underlying code as needed.
Multilingual capabilities: Qwen is equipped to comprehend and translate several languages, including English, Chinese, and French.
Versatile functionalities: In addition to language generation and translation, Qwen models excel in tasks such as answering questions, summarizing texts, and generating code, making them highly adaptable tools for various applications. Overall, the Qwen LLM family stands out for its extensive capabilities and flexibility in meeting user needs.
API Access
Has API
API Access
Has API
Screenshots View All
No images available
Integrations
16x Prompt
Aim
Alibaba Cloud
Azure AI Foundry Agent Service
C
CSS
Clojure
CoTrader
CodeNext
Cranium
Integrations
16x Prompt
Aim
Alibaba Cloud
Azure AI Foundry Agent Service
C
CSS
Clojure
CoTrader
CodeNext
Cranium
Pricing Details
$0.0004 per 1000 tokens
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
Microsoft
Founded
1975
Country
United States
Website
azure.microsoft.com/en-us/products/cognitive-services/openai-service
Vendor Details
Company Name
Alibaba
Founded
1999
Country
China
Website
github.com/QwenLM/Qwen
Product Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Natural Language Generation
Business Intelligence
CRM Data Analysis and Reports
Chatbot
Email Marketing
Financial Reporting
Multiple Language Support
SEO
Web Content
Natural Language Processing
Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization