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Description

Instruction-following models like GPT-3.5 (text-DaVinci-003), ChatGPT, Claude, and Bing Chat have seen significant advancements in their capabilities, leading to a rise in their usage among individuals in both personal and professional contexts. Despite their growing popularity and integration into daily tasks, these models are not without their shortcomings, as they can sometimes disseminate inaccurate information, reinforce harmful stereotypes, and use inappropriate language. To effectively tackle these critical issues, it is essential for researchers and scholars to become actively involved in exploring these models further. However, conducting research on instruction-following models within academic settings has posed challenges due to the unavailability of models with comparable functionality to proprietary options like OpenAI’s text-DaVinci-003. In response to this gap, we are presenting our insights on an instruction-following language model named Alpaca, which has been fine-tuned from Meta’s LLaMA 7B model, aiming to contribute to the discourse and development in this field. This initiative represents a step towards enhancing the understanding and capabilities of instruction-following models in a more accessible manner for researchers.

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.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Llama
1min.AI
BERT
BLACKBOX AI
ChatGPT
CodeQwen
Deep Infra
Dolly
GPT-4
IONOS Cloud AI Model Hub
Llama 3
Llama 3.1
Llama 3.2
Llama 3.3
Ludwig
Meta AI
Pipeshift
Stable LM
Tabby

Integrations

Llama
1min.AI
BERT
BLACKBOX AI
ChatGPT
CodeQwen
Deep Infra
Dolly
GPT-4
IONOS Cloud AI Model Hub
Llama 3
Llama 3.1
Llama 3.2
Llama 3.3
Ludwig
Meta AI
Pipeshift
Stable LM
Tabby

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Stanford Center for Research on Foundation Models (CRFM)

Country

United States

Website

crfm.stanford.edu/2023/03/13/alpaca.html

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

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

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Alternatives

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