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Average Ratings 0 Ratings

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ease
features
design
support

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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

StableVicuna represents the inaugural large-scale open-source chatbot developed through reinforced learning from human feedback (RLHF). It is an advanced version of the Vicuna v0 13b model, which has undergone further instruction fine-tuning and RLHF training. To attain the impressive capabilities of StableVicuna, we use Vicuna as the foundational model and adhere to the established three-stage RLHF framework proposed by Steinnon et al. and Ouyang et al. Specifically, we perform additional training on the base Vicuna model with supervised fine-tuning (SFT), utilizing a blend of three distinct datasets. The first is the OpenAssistant Conversations Dataset (OASST1), which consists of 161,443 human-generated messages across 66,497 conversation trees in 35 languages. The second dataset is GPT4All Prompt Generations, encompassing 437,605 prompts paired with responses created by GPT-3.5 Turbo. Lastly, the Alpaca dataset features 52,000 instructions and demonstrations that were produced using OpenAI's text-davinci-003 model. This collective approach to training enhances the chatbot's ability to engage effectively in diverse conversational contexts.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

1min.AI Yes 
BLACKBOX AI Yes 
CodeQwen Yes 
Deep Infra Yes 
IONOS Cloud AI Model Hub Yes 
Llama Yes 
Llama 2 Yes 
Llama 3 Yes 
Llama 3.1 Yes 
Llama 3.2 Yes 
Llama 3.3 Yes 
Meta AI Yes 
Ollama Yes 
Pipeshift Yes 
Prefactor Yes 
Tabby Yes 

Integrations

1min.AI No 
BLACKBOX AI No 
CodeQwen No 
Deep Infra No 
IONOS Cloud AI Model Hub No 
Llama No 
Llama 2 No 
Llama 3 No 
Llama 3.1 No 
Llama 3.2 No 
Llama 3.3 No 
Meta AI No 
Ollama No 
Pipeshift No 
Prefactor No 
Tabby No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

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 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 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

Stability AI

Founded

2019

Country

United Kingdom

Website

stability.ai/

Product Features

Artificial Intelligence

Chatbot No 
For Healthcare No 
For Sales No 
For eCommerce No 
Image Recognition No 
Machine Learning No 
Multi-Language No 
Natural Language Processing No 
Predictive Analytics No 
Process/Workflow Automation No 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

Chatbot

Call to Action No 
Context and Coherence No 
Human Takeover No 
Inline Media / Videos No 
Machine Learning No 
Natural Language Processing No 
Payment Integration No 
Prediction No 
Ready-made Templates No 
Reporting / Analytics No 
Sentiment Analysis No 
Social Media Integration No 

Conversational AI

Code-free Development No 
Contextual Guidance No 
For Developers No 
Intent Recognition No 
Multi-Languages No 
Omni-Channel No 
On-Screen Chats No 
Pre-configured Bot No 
Reusable Components No 
Sentiment Analysis No 
Speech Recognition No 
Speech Synthesis No 
Virtual Assistant No 

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