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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

The GPT-4 model represents a significant advancement in AI, being a large multimodal system capable of handling both text and image inputs while producing text outputs, which allows it to tackle complex challenges with a level of precision unmatched by earlier models due to its extensive general knowledge and enhanced reasoning skills. Accessible through the OpenAI API for subscribers, GPT-4 is also designed for chat interactions, similar to gpt-3.5-turbo, while proving effective for conventional completion tasks via the Chat Completions API. This state-of-the-art version of GPT-4 boasts improved features such as better adherence to instructions, JSON mode, consistent output generation, and the ability to call functions in parallel, making it a versatile tool for developers. However, it is important to note that this preview version is not fully prepared for high-volume production use, as it has a limit of 4,096 output tokens. Users are encouraged to explore its capabilities while keeping in mind its current limitations.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

ChatGPT
GPT-4
302.AI
AIForAll
BERT
Calypso
ChatArt Pro
ChatGPT Plus
DeftGPT
Dolly
Expanse
Glowbom
Koala AI
Launch Leopard
Llama
Moemate
OpenAI
Prompt Refine
RoboCoder
Wordware

Integrations

ChatGPT
GPT-4
302.AI
AIForAll
BERT
Calypso
ChatArt Pro
ChatGPT Plus
DeftGPT
Dolly
Expanse
Glowbom
Koala AI
Launch Leopard
Llama
Moemate
OpenAI
Prompt Refine
RoboCoder
Wordware

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$0.0200 per 1000 tokens
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

OpenAI

Founded

2015

Country

United States

Website

platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo

Product Features

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)

Natural Language Generation

Business Intelligence
CRM Data Analysis and Reports
Chatbot
Email Marketing
Financial Reporting
Multiple Language Support
SEO
Web Content

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

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