AlphaCodeGoogle DeepMind
|
Code LlamaMeta
|
|||||
Related Products
|
||||||
About
Creating solutions to unforeseen problems is second nature in human intelligence, a result of critical thinking informed by experience. The machine learning community has made tremendous progress in generating and understanding textual data, but advances in problem-solving remain limited to relatively simple maths and programming problems, or else retrieving and copying existing solutions. As part of DeepMind’s mission to solve intelligence, we created a system called AlphaCode that writes computer programs at a competitive level. AlphaCode achieved an estimated rank within the top 54% of participants in programming competitions by solving new problems that require a combination of critical thinking, logic, algorithms, coding, and natural language understanding. AlphaCode uses transformer-based language models to generate code at an unprecedented scale, and then smartly filters to a small set of promising programs.
|
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.
|
|||||
Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
|||||
Audience
Developers and anyone seeking a solution to generate code and improve their algorithms
|
Audience
Users interested in a powerful, free, open source large language model for coding
|
|||||
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
|
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Not Supported
|
|||||
API
Offers API
Not Supported
|
API
Offers API
Not Supported
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
|
Pricing
Free
Open source
Free Version
Supported
Free Trial
Not Supported
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Supported
Webinars
Supported
Live Online
Not Supported
In Person
Not Supported
|
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
|
|||||
Company InformationGoogle DeepMind
United States
www.deepmind.com/blog/competitive-programming-with-alphacode
|
Company InformationMeta
Founded: 2004
United States
ai.meta.com/blog/code-llama-large-language-model-coding/
|
|||||
Alternatives |
Alternatives |
|||||
|
|
|
|||||
|
|
|
|||||
|
|
|
|||||
|
|
|
|||||
Categories |
Categories |
|||||
Integrations
1min.AI
Not Supported
BLACKBOX AI
Not Supported
C++
Supported
CodeQwen
Not Supported
Deep Infra
Not Supported
GitHub
Supported
Google Skills
Supported
IONOS Cloud AI Model Hub
Not Supported
Llama
Not Supported
Llama 2
Not Supported
|
Integrations
1min.AI
Supported
BLACKBOX AI
Supported
C++
Not Supported
CodeQwen
Supported
Deep Infra
Supported
GitHub
Not Supported
Google Skills
Not Supported
IONOS Cloud AI Model Hub
Supported
Llama
Supported
Llama 2
Supported
|
|||||
|
|
|