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What is Llama 3?

We have integrated Llama 3 into Meta AI, our smart assistant that transforms the way people perform tasks, innovate, and interact with technology. By leveraging Meta AI for coding and troubleshooting, users can directly experience the power of Llama 3. Whether you are developing agents or other AI-based solutions, Llama 3, which is offered in both 8B and 70B variants, delivers the essential features and adaptability needed to turn your concepts into reality. In conjunction with the launch of Llama 3, we have updated our Responsible Use Guide (RUG) to provide comprehensive recommendations on the ethical development of large language models. Our approach focuses on enhancing trust and safety measures, including the introduction of Llama Guard 2, which aligns with the newly established taxonomy from MLCommons and expands its coverage to include a broader range of safety categories, alongside code shield and Cybersec Eval 2. Moreover, these improvements are designed to promote a safer and more responsible application of AI technologies across different fields, ensuring that users can confidently harness these innovations. The commitment to ethical standards reflects our dedication to fostering a secure and trustworthy AI environment.

What is CodeQwen?

CodeQwen acts as the programming equivalent of Qwen, a collection of large language models developed by the Qwen team at Alibaba Cloud. This model, which is based on a transformer architecture that operates purely as a decoder, has been rigorously pre-trained on an extensive dataset of code. It is known for its strong capabilities in code generation and has achieved remarkable results on various benchmarking assessments. CodeQwen can understand and generate long contexts of up to 64,000 tokens and supports 92 programming languages, excelling in tasks such as text-to-SQL queries and debugging operations. Interacting with CodeQwen is uncomplicated; users can start a dialogue with just a few lines of code leveraging transformers. The interaction is rooted in creating the tokenizer and model using pre-existing methods, utilizing the generate function to foster communication through the chat template specified by the tokenizer. Adhering to our established guidelines, we adopt the ChatML template specifically designed for chat models. This model efficiently completes code snippets according to the prompts it receives, providing responses that require no additional formatting changes, thereby significantly enhancing the user experience. The smooth integration of these components highlights the adaptability and effectiveness of CodeQwen in addressing a wide range of programming challenges, making it an invaluable tool for developers.

Media

Media

Integrations Supported

Code Llama
Python
AiAssistWorks
AnythingLLM
Azure Marketplace
C
Coginiti
Cyte
Kerlig
Mammouth AI
MindMac
Msty
R
Roost.ai
Scala
YouPro

Integrations Supported

Code Llama
Python
AtCoder
Conda
GPT-3.5
LangChain

API Availability

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

Free
Free Version

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Not specified

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

llama.meta.com

Company Facts

Organization Name

Alibaba

Date Founded

1999

Company Location

China

Company Website

github.com/QwenLM/CodeQwen1.5

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Code Refactoring

Not specified

AI Coding Assistants

Not specified

AI Coding Models

Not specified

AI Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

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