BERT

BERT

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About

Apply advanced coding and language models to a variety of use cases. Leverage large-scale, generative AI models with deep understandings of language and code to enable new reasoning and comprehension capabilities for building cutting-edge applications. Apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data. Detect and mitigate harmful use with built-in responsible AI and access enterprise-grade Azure security. Gain access to generative models that have been pretrained with trillions of words. Apply them to new scenarios including language, code, reasoning, inferencing, and comprehension. Customize generative models with labeled data for your specific scenario using a simple REST API. Fine-tune your model's hyperparameters to increase accuracy of outputs. Use the few-shot learning capability to provide the API with examples and achieve more relevant results.

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.

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

Organizations that want to power their apps with large-scale AI models

Audience

Developers interested in a powerful large language model

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

$0.0004 per 1000 tokens
Pricing is based on a pay-as-you-go consumption model with a price per unit for each model.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

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

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Reviews/Ratings

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

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

Microsoft
Founded: 1975
United States
azure.microsoft.com/en-us/products/cognitive-services/openai-service

Company Information

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

Alternatives

Alternatives

Gemini

Gemini

Google
ALBERT

ALBERT

Google
BLOOM

BLOOM

BigScience
Cohere

Cohere

Cohere AI
RoBERTa

RoBERTa

Meta
GPT-4

GPT-4

OpenAI

Categories

Categories

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Integrations

Alpaca
BotDojo
CodeNext
Continue
Cranium
Doable.sh
Fleece AI
GPT-5
GPT-5.1
GPT-5.3 Instant
GPT-5.4 nano
GPT-5.5
GPT-6
Ivo
Kore.ai
Leo
Opik
Parasoft
Snowflake Cortex AI
Tune AI
Claim Azure OpenAI Service and update features and information
Claim Azure OpenAI Service and update features and information
Claim BERT and update features and information
Claim BERT and update features and information