BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering Reviews 2025: Details, Pricing, & Features

RJ

Rishika J.

Software Engineer II

Mid-Market (51-1000 emp.)

4/13/2022

"BERT: A question answering model by PyTorch"

4/5

What do you like best about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

One of the best parts about this particular PyTorch transformer is its support for more than 100 languages. BERT is integrated with the most efficient neural networks, training objectives, and transfer learning. It is a pre-trained model with highly accurate tuning trained on different datasets available like SQUAD. It answers the questions concisely and even helps in other use cases like highlighting paragraphs with crucial entry points when a question is asked. Review collected by and hosted on G2.com.

What do you dislike about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

The accuracy and the vast support for large datasets for different languages make BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering an expensive model. Due to the large dataset, this model is a bit slow to train, requires updating a lot of weights, and takes more computation time. Review collected by and hosted on G2.com.

What problems is BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering solving and how is that benefiting you?

With BERT, my organization aimed to understand and learn implementations of Natural Language Processing (NLP) in daily use cases. We used this model to help answer the frequently asked questions by the customers from the context documentation. Since the model supports so many languages and is trained using vast datasets, it really helped to concisely answer the questions from the context provided even when it was not present in the data set it used while training. Review collected by and hosted on G2.com.

JP

Jagadis P.

Product Specialist (Order to Cash)

Enterprise (> 1000 emp.)

4/7/2022

"Mastering your setup with PyTorch - Master piece"

4/5

What do you like best about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

Pytorch BERT is one of the most Extractive question answering tools which is created on a text embedding idealogy. This takes as input a pair of question-setup strings and returns a related contextual sub-module string that more or less matches the exact context of the real answer to the question. The best part of this setup is it is based on a pre-trained on multilingual setup which helps in returning question-context strings. Review collected by and hosted on G2.com.

What do you dislike about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

AI & ML is doing marvelous jobs but still, we have not achieved the level that we want. Sometimes it acts weird by returning an answer or string which is related to the question in a vocabulary way but not a contextual way. This can be set aside as an exception because these are very rare instances where your utterances are not set properly. Review collected by and hosted on G2.com.

What problems is BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering solving and how is that benefiting you?

One of the best things that this tool is helping us with is its multilingual setup. Also, its pre-trained model set up in multiple languages is helping with masked language modeling. This is very strong, as it also helps in checking raw or unstructured setup. Review collected by and hosted on G2.com.

TN

Tarang N.

Systems Associate - Trainee

Mid-Market (51-1000 emp.)

4/11/2022

"BERT: A unicase for Multilingual Base Model"

4/5

What do you like best about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

BERT Base Multilingual Uncased PyTorch Hub is a transformer model as it helps the computer to understand the multilingual data of different languages into one unicase form and predict the next sentence for the betterment with the help of artificial intelligence and then randomly masking some part of the words and run it to complete the whole sentence. Review collected by and hosted on G2.com.

What do you dislike about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

There isn't any thing that I don't like about BERT Base Multilingual but it is primarily worked for fine tuned on task that use the whole sentence to make decision and sequence classification. Review collected by and hosted on G2.com.

UI

Verified User in Information Technology and Services

Small-Business (50 or fewer emp.)

4/6/2022

"Natural language processing Model"

4/5

What do you like best about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

BERT is a multilingual base model, it is trained over 102 languages. The advantage of the model is that it is uncased. One can easily access it using pytorch library. The model aims to fine tuned the tasks which depends on whole sentences. Review collected by and hosted on G2.com.

What do you dislike about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

The model seems to be quite efficient and effective. Didn't find any drawback Review collected by and hosted on G2.com.

II

Verified User in Information Technology and Services

Enterprise (> 1000 emp.)

5/20/2022

"BERT BASE - Works Perfectly well"

4.5/5

What do you like best about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

Language Model Tokenizer. It works well with all sets of data and in all generic industries. Review collected by and hosted on G2.com.

What do you dislike about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

Difficult to accomplish tasks in a limited time. Time consuming. Review collected by and hosted on G2.com.

BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering Reviews & Product Details

BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering Overview

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5 BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering Reviews

Rishika J.

"BERT: A question answering model by PyTorch"

What do you like best about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

What do you dislike about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

What problems is BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering solving and how is that benefiting you?

Jagadis P.

"Mastering your setup with PyTorch - Master piece"

What do you like best about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

What do you dislike about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

What problems is BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering solving and how is that benefiting you?

Tarang N.

"BERT: A unicase for Multilingual Base Model"

What do you like best about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

What do you dislike about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

What problems is BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering solving and how is that benefiting you?

Verified User in Information Technology and Services

"Natural language processing Model"

What do you like best about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

What do you dislike about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

What problems is BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering solving and how is that benefiting you?

Verified User in Information Technology and Services

"BERT BASE - Works Perfectly well"

What do you like best about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

What do you dislike about BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering?

What problems is BERT Base Multilingual Uncased PyTorch Hub Extractive Question Answering solving and how is that benefiting you?

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