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ease
features
design
support

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Description

The AI is designed to embody a character capable of engaging in discussions on virtually any subject! Take some time to interact with them! This initial version is seeking your assistance. Engage in a dialogue about any topic that piques your interest, and please share your thoughts to aid in the advancement of AI research. The system is built upon a sophisticated language model that utilizes publicly sourced text for its foundation. For more intricate insights into its functionality, you can refer to our recent blog post, while additional specifics regarding the datasets involved are available in our model cards. Furthermore, the bot enhances its understanding through web searches and leverages its long-term memory, which encapsulates prior conversations you've had with it. When the “look inside” option appears during your chat, you can view and even reset these memories at your convenience. Additionally, clicking on a message allows you to access further details about its creation, including the search queries utilized by the bot. This transparency aims to foster a richer interaction experience.

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

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

Free
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

Meta

Founded

2004

Country

United States

Website

BlenderBot.ai

Vendor Details

Company Name

Stability AI

Founded

2019

Country

United Kingdom

Website

stability.ai/

Product Features

Conversational AI

Code-free Development
Contextual Guidance
For Developers
Intent Recognition
Multi-Languages
Omni-Channel
On-Screen Chats
Pre-configured Bot
Reusable Components
Sentiment Analysis
Speech Recognition
Speech Synthesis
Virtual Assistant

Product Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Chatbot

Call to Action
Context and Coherence
Human Takeover
Inline Media / Videos
Machine Learning
Natural Language Processing
Payment Integration
Prediction
Ready-made Templates
Reporting / Analytics
Sentiment Analysis
Social Media Integration

Conversational AI

Code-free Development
Contextual Guidance
For Developers
Intent Recognition
Multi-Languages
Omni-Channel
On-Screen Chats
Pre-configured Bot
Reusable Components
Sentiment Analysis
Speech Recognition
Speech Synthesis
Virtual Assistant

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