BERT

BERT

Google
OPT

OPT

Meta
+
+

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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

Large language models, which are often trained for hundreds of thousands of compute days, have shown remarkable capabilities for zero- and few-shot learning. Given their computational cost, these models are difficult to replicate without significant capital. For the few that are available through APIs, no access is granted to the full model weights, making them difficult to study. We present Open Pre-trained Transformers (OPT), a suite of decoder-only pre-trained transformers ranging from 125M to 175B parameters, which we aim to fully and responsibly share with interested researchers. We show that OPT-175B is comparable to GPT-3, while requiring only 1/7th the carbon footprint to develop. We are also releasing our logbook detailing the infrastructure challenges we faced, along with code for experimenting with all of the released models.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Developers interested in a powerful large language model

Audience

AI developers interested in a large language model

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

API

Offers API Not Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

No images available

Pricing

Free
Free Version Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

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 Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

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

Company Information

Meta
Founded: 2004
United States
www.meta.com

Alternatives

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Llama 2

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Categories

Categories

AI Models Supported

Integrations

AWS Marketplace Supported
Alpaca Supported
Amazon SageMaker Model Training Supported
Gopher Supported
Haystack Supported
PostgresML Supported
Spark NLP Supported

Integrations

AWS Marketplace Not Supported
Alpaca Not Supported
Amazon SageMaker Model Training Not Supported
Gopher Not Supported
Haystack Not Supported
PostgresML Not Supported
Spark NLP Not Supported
Claim BERT and update features and information
Claim BERT and update features and information
Claim OPT and update features and information
Claim OPT and update features and information