BERT

BERT

Google
PaLM

PaLM

Google
+
+

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About

BERT is a large language model and a method of pre-training language representations. Pre-training refers to how BERT is first trained on a large source of text, such as Wikipedia. You can then apply the training results to other Natural Language Processing (NLP) tasks, such as question answering and sentiment analysis. With BERT and AI Platform Training, you can train a variety of NLP models in about 30 minutes.

About

PaLM API is an easy and safe way to build on top of our best language models. Today, we’re making an efficient model available, in terms of size and capabilities, and we’ll add other sizes soon. The API also comes with an intuitive tool called MakerSuite, which lets you quickly prototype ideas and, over time, will have features for prompt engineering, synthetic data generation and custom-model tuning — all supported by robust safety tools. Select developers can access the PaLM API and MakerSuite in Private Preview today, and stay tuned for our waitlist soon.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers interested in a powerful large language model

Audience

AI developers interested in a large language model accessible via API

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 4.0 / 5
ease 4.0 / 5
features 4.0 / 5
design 3.0 / 5
support 3.0 / 5

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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Pros & Cons from Real Users

Pros

  • When BERT model implemented on stress detection use case, BERT as it handles context of the text was easily able to identify negation sentence like detecting "I am NOT happy" as a stressful text which was not happening in other models like logistic regression, decision tree, random forest, multinomial naive bayes, CNN, RNN, LSTM etc.

Cons

  • difficulty in finding a suitable multilingual datastet to train the model for both hind and english use cases.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Google
Founded: 1998
United States
cloud.google.com/ai-platform/training/docs/algorithms/bert-start

Company Information

Google
Founded: 1998
United States
google.com

Alternatives

Gemini

Gemini

Google

Alternatives

Dolly

Dolly

Databricks
ALBERT

ALBERT

Google
mT5

mT5

Google
BLOOM

BLOOM

BigScience
PaLM 2

PaLM 2

Google
RoBERTa

RoBERTa

Meta
GPT-4

GPT-4

OpenAI

Categories

Categories

Integrations

AWS Marketplace
Alpaca
Amazon SageMaker Model Training
ChatGOT
Gemini Enterprise Agent Platform
Gopher
Haystack
MakerSuite
PostgresML
Spark NLP
TextFX
WrangleAI

Integrations

AWS Marketplace
Alpaca
Amazon SageMaker Model Training
ChatGOT
Gemini Enterprise Agent Platform
Gopher
Haystack
MakerSuite
PostgresML
Spark NLP
TextFX
WrangleAI
Claim BERT and update features and information
Claim BERT and update features and information
Claim PaLM and update features and information
Claim PaLM and update features and information