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Description
The GPT-3.5 series represents an advancement in OpenAI's large language models, building on the capabilities of its predecessor, GPT-3.
These models excel at comprehending and producing human-like text, with four primary variations designed for various applications. The core GPT-3.5 models are intended to be utilized through the text completion endpoint, while additional models are optimized for different endpoint functionalities. Among these, the Davinci model family stands out as the most powerful, capable of executing any task that the other models can handle, often requiring less detailed input. For tasks that demand a deep understanding of context, such as tailoring summaries for specific audiences or generating creative content, the Davinci model tends to yield superior outcomes. However, this enhanced capability comes at a cost, as Davinci requires more computing resources, making it pricier for API usage and slower compared to its counterparts. Overall, the advancements in GPT-3.5 not only improve performance but also expand the range of potential applications.
Description
RoBERTa enhances the language masking approach established by BERT, where the model is designed to predict segments of text that have been deliberately concealed within unannotated language samples. Developed using PyTorch, RoBERTa makes significant adjustments to BERT's key hyperparameters, such as eliminating the next-sentence prediction task and utilizing larger mini-batches along with elevated learning rates. These modifications enable RoBERTa to excel in the masked language modeling task more effectively than BERT, resulting in superior performance in various downstream applications. Furthermore, we examine the benefits of training RoBERTa on a substantially larger dataset over an extended duration compared to BERT, incorporating both existing unannotated NLP datasets and CC-News, a new collection sourced from publicly available news articles. This comprehensive approach allows for a more robust and nuanced understanding of language.
API Access
Has API
Yes
API Access
Has API
No
Integrations
AI Buster
Yes
AiAssistWorks
Yes
Alicent
Yes
AlphaCorp
Yes
ChatArt Pro
Yes
ChatGPT
Yes
CodeQwen
Yes
Entry Point AI
Yes
Grail Writer
Yes
InlineGPT
Yes
Integrations
AI Buster
No
AiAssistWorks
No
Alicent
No
AlphaCorp
No
ChatArt Pro
No
ChatGPT
No
CodeQwen
No
Entry Point AI
No
Grail Writer
No
InlineGPT
No
Pricing Details
$0.0200 per 1000 tokens
Prices are per 1,000 tokens. You can think of tokens as pieces of words, where 1,000 tokens is about 750 words. This paragraph is 35 tokens.
Free Trial
Yes
Free Version
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
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
Yes
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
OpenAI
Founded
2015
Country
United States
Website
openai.com
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
ai.facebook.com/blog/roberta-an-optimized-method-for-pretraining-self-supervised-nlp-systems/
Product Features
Artificial Intelligence
Chatbot
Yes
For Healthcare
Yes
For Sales
Yes
For eCommerce
Yes
Image Recognition
No
Machine Learning
Yes
Multi-Language
Yes
Natural Language Processing
Yes
Predictive Analytics
No
Process/Workflow Automation
No
Rules-Based Automation
No
Virtual Personal Assistant (VPA)
Yes
Natural Language Generation
Business Intelligence
No
CRM Data Analysis and Reports
No
Chatbot
Yes
Email Marketing
No
Financial Reporting
No
Multiple Language Support
Yes
SEO
Yes
Web Content
Yes
Natural Language Processing
Co-Reference Resolution
Yes
In-Database Text Analytics
Yes
Named Entity Recognition
Yes
Natural Language Generation (NLG)
Yes
Open Source Integrations
Yes
Parsing
Yes
Part-of-Speech Tagging
Yes
Sentence Segmentation
Yes
Stemming/Lemmatization
Yes
Tokenization
Yes