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Description

CodeQwen serves as the coding counterpart to Qwen, which is a series of large language models created by the Qwen team at Alibaba Cloud. Built on a transformer architecture that functions solely as a decoder, this model has undergone extensive pre-training using a vast dataset of code. It showcases robust code generation abilities and demonstrates impressive results across various benchmarking tests. With the capacity to comprehend and generate long contexts of up to 64,000 tokens, CodeQwen accommodates 92 programming languages and excels in tasks such as text-to-SQL queries and debugging. Engaging with CodeQwen is straightforward—you can initiate a conversation with just a few lines of code utilizing transformers. The foundation of this interaction relies on constructing the tokenizer and model using pre-existing methods, employing the generate function to facilitate dialogue guided by the chat template provided by the tokenizer. In alignment with our established practices, we implement the ChatML template tailored for chat models. This model adeptly completes code snippets based on the prompts it receives, delivering responses without the need for any further formatting adjustments, thereby enhancing the user experience. The seamless integration of these elements underscores the efficiency and versatility of CodeQwen in handling diverse coding tasks.

Description

OpenEuroLLM represents a collaborative effort between prominent AI firms and research organizations across Europe, aimed at creating a suite of open-source foundational models to promote transparency in artificial intelligence within the continent. This initiative prioritizes openness by making data, documentation, training and testing code, and evaluation metrics readily available, thereby encouraging community participation. It is designed to comply with European Union regulations, with the goal of delivering efficient large language models that meet the specific standards of Europe. A significant aspect of the project is its commitment to linguistic and cultural diversity, ensuring that multilingual capabilities cover all official EU languages and potentially more. The initiative aspires to broaden access to foundational models that can be fine-tuned for a range of applications, enhance evaluation outcomes across different languages, and boost the availability of training datasets and benchmarks for researchers and developers alike. By sharing tools, methodologies, and intermediate results, transparency is upheld during the entire training process, fostering trust and collaboration within the AI community. Ultimately, OpenEuroLLM aims to pave the way for more inclusive and adaptable AI solutions that reflect the rich diversity of European languages and cultures.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Alibaba Cloud Yes 
AtCoder Yes 
Code Llama Yes 
Codeforces Yes 
Conda Yes 
DeepSeek Coder Yes 
GPT-3.5 Yes 
GPT-4 Yes 
Hugging Face Yes 
LangChain Yes 
LeetCode Yes 
LlamaIndex Yes 
ModelScope Yes 
Ollama Yes 
PyTorch Yes 
Python Yes 
Qwen Studio Yes 
StarCoder Yes 

Integrations

Alibaba Cloud No 
AtCoder No 
Code Llama No 
Codeforces No 
Conda No 
DeepSeek Coder No 
GPT-3.5 No 
GPT-4 No 
Hugging Face No 
LangChain No 
LeetCode No 
LlamaIndex No 
ModelScope No 
Ollama No 
PyTorch No 
Python No 
Qwen Studio No 
StarCoder No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

github.com/QwenLM/CodeQwen1.5

Vendor Details

Company Name

OpenEuroLLM

Website

openeurollm.eu/

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