Average Ratings 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

No User Reviews. Be the first to provide a review:

Write a Review

Description

Code Llama is an advanced language model designed to generate code through text prompts, distinguishing itself as a leading tool among publicly accessible models for coding tasks. This innovative model not only streamlines workflows for existing developers but also aids beginners in overcoming challenges associated with learning to code. Its versatility positions Code Llama as both a valuable productivity enhancer and an educational resource, assisting programmers in creating more robust and well-documented software solutions. Additionally, users can generate both code and natural language explanations by providing either type of prompt, making it an adaptable tool for various programming needs. Available for free for both research and commercial applications, Code Llama is built upon Llama 2 architecture and comes in three distinct versions: the foundational Code Llama model, Code Llama - Python which is tailored specifically for Python programming, and Code Llama - Instruct, optimized for comprehending and executing natural language directives effectively.

Description

Llama (Large Language Model Meta AI) stands as a cutting-edge foundational large language model aimed at helping researchers push the boundaries of their work within this area of artificial intelligence. By providing smaller yet highly effective models like Llama, the research community can benefit even if they lack extensive infrastructure, thus promoting greater accessibility in this dynamic and rapidly evolving domain. Creating smaller foundational models such as Llama is advantageous in the landscape of large language models, as it demands significantly reduced computational power and resources, facilitating the testing of innovative methods, confirming existing research, and investigating new applications. These foundational models leverage extensive unlabeled datasets, making them exceptionally suitable for fine-tuning across a range of tasks. We are offering Llama in multiple sizes (7B, 13B, 33B, and 65B parameters), accompanied by a detailed Llama model card that outlines our development process while adhering to our commitment to Responsible AI principles. By making these resources available, we aim to empower a broader segment of the research community to engage with and contribute to advancements in AI.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

No images available

Integrations

1min.AI Yes 
Deep Infra Yes 
Meta AI Yes 
Ollama Yes 
Prefactor Yes 
AiAssistWorks No 
EaseMate AI No 
LLaMA-Factory No 
Llama Yes 
Llama 4 Maverick No 
Overseer AI No 
Plano No 
Prompt Genie No 
Ragas No 
RagmyAI No 
Revere No 
TypeThink No 
amazee.ai No 
kluster.ai No 

Integrations

1min.AI Yes 
Deep Infra Yes 
Meta AI Yes 
Ollama Yes 
Prefactor Yes 
AiAssistWorks Yes 
EaseMate AI Yes 
LLaMA-Factory Yes 
Llama No 
Llama 4 Maverick Yes 
Overseer AI Yes 
Plano Yes 
Prompt Genie Yes 
Ragas Yes 
RagmyAI Yes 
Revere Yes 
TypeThink Yes 
amazee.ai Yes 
kluster.ai Yes 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

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

Deployment

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

Customer Support

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

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

ai.meta.com/blog/code-llama-large-language-model-coding/

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

www.llama.com

Alternatives

CodeGemma Reviews

CodeGemma

Google

Alternatives

Mistral AI Reviews

Mistral AI

5.0 out of 5 stars
GitHub Copilot Reviews

GitHub Copilot

GitHub
4.0 out of 5 stars
Gemini Reviews

Gemini

Google
5.0 out of 5 stars
Llama 2 Reviews

Llama 2

Meta
CodeQwen Reviews

CodeQwen

Alibaba
Alpaca Reviews

Alpaca

Stanford Center for Research on Foundation Models (CRFM)