Related Products
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About
Code Llama is a large language model (LLM) that can use text prompts to generate code. Code Llama is state-of-the-art for publicly available LLMs on code tasks, and has the potential to make workflows faster and more efficient for current developers and lower the barrier to entry for people who are learning to code. Code Llama has the potential to be used as a productivity and educational tool to help programmers write more robust, well-documented software.
Code Llama is a state-of-the-art LLM capable of generating code, and natural language about code, from both code and natural language prompts.
Code Llama is free for research and commercial use.
Code Llama is built on top of Llama 2 and is available in three models:
Code Llama, the foundational code model;
Codel Llama - Python specialized for Python;
and Code Llama - Instruct, which is fine-tuned for understanding natural language instructions.
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About
Wing Python IDE was designed from the ground up for Python, to bring you a more productive development experience. Type less and let Wing worry about the details. Get immediate feedback by writing your Python code interactively in the live runtime. Easily navigate code and documentation. Avoid common errors and find problems early with assistance from Wing's deep Python code analysis. Keep code clean with smart refactoring and code quality inspection. Debug any Python code. Inspect debug data and try out bug fixes interactively without restarting your app. Work locally or on a remote host, VM, or container. Wingware's 21 years of Python IDE experience bring you a more Pythonic development environment. Wing was designed from the ground up for Python, written in Python, and is extensible with Python. So you can be more productive.
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About
All URL parts, scheme, user, password, host, port, path, query, and fragment are accessible by properties. All URL manipulations produce a new URL object. Strings passed to constructor and modification methods are automatically encoded giving canonical representation as result. Regular properties are percent-decoded, use raw_ versions for getting encoded strings. Human-readable representation of URL is available as .human_repr(). PyPI contains binary wheels for Linux, Windows and MacOS. If you want to install yarl on another operating system (like Alpine Linux, which is not manylinux-compliant because of the missing glibc and therefore, cannot be used with our wheels) the tarball will be used to compile the library from the source code. It requires a C compiler and Python headers installed. Please note that the pure-Python (uncompiled) version is much slower. However, PyPy always uses a pure-Python implementation, and, as such, it is unaffected by this variable.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Users interested in a powerful, free, open source large language model for coding
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Audience
Python developers seeking a tool to build applications
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Audience
Developers, professionals, companies and individuals seeking a solution offering a URL library solution
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationMeta
Founded: 2004
United States
ai.meta.com/blog/code-llama-large-language-model-coding/
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Company InformationWingware
Founded: 1999
United States
wingware.com
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Company InformationPython Software Foundation
United States
pypi.org/project/yarl/
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Categories |
Categories |
Categories |
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Application Development Features
Access Controls/Permissions
Code Assistance
Code Refactoring
Collaboration Tools
Compatibility Testing
Data Modeling
Debugging
Deployment Management
Graphical User Interface
Mobile Development
No-Code
Reporting/Analytics
Software Development
Source Control
Testing Management
Version Control
Web App Development
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Integrations
1min.AI
Apache Subversion
C
C++
CodeQwen
Django
Docker
Google App Engine
Llama
Llama 3
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Integrations
1min.AI
Apache Subversion
C
C++
CodeQwen
Django
Docker
Google App Engine
Llama
Llama 3
|
Integrations
1min.AI
Apache Subversion
C
C++
CodeQwen
Django
Docker
Google App Engine
Llama
Llama 3
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