Questions tagged [language-model]

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Effect of discounting parameter on Language Model Perplexity

The general formula for absolute discounting for calculating language model probabilities subtracts a discounting parameter d from the count of the ngram before calculating the probabilities. The ...
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How to use transformers to build a Query Auto-Completion Engine? [closed]

I'm working on building a Query Auto-Completion engine using deep learning. I learned that transformers can be used for text generation. I'm looking for some intuition for this task.
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Is there a way to find difference between topics in two languages using nlp

I want to analyse queries and their differences between two different languages English and Spanish in this case. I'm aware about topic modelling. I'm in search of any corpus available or any ...
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7 views

Dirichlet smoothing as an IDF component

How can Dirichlet smoothing be used as an IDF component to estimate the probabilities of a Topic model ? i.e, Smoothing with a background collection model to estimate topic model ? I've seen many ...
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1answer
17 views

Generate text using user-supplied keywords

I've got a use case where I need to generate sentences based on a set of user supplied keywords. Here is an example of what I need: User input: End-User: Data Scientists Region: Middle East ...
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1answer
224 views

Is BERT a language model?

Is BERT a language model in the sense of a function that gets a sentence and returns a probability? I know its main usage is sentence embedding, but can it also provide this functionality?
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Comparing Language Model of two corpora

I know using Conditional Language Model I can learn the probability of a sentence given the corpus I used to train my model. I will then be able to generate meaningful text by sampling from the ...
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8 views

How to convert subword PPL to word level PPL?

I'm using this formula to covert subword perpexity to word perplexity: PPL_word = exp(log(PPL_subword) * num_subwords / num_words) The question is do I need to ...
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How can I make a whitespace tokenizer and use it to build a language model from scratch using transformers

I have raised a ticket in github, whose link is here Which has a problem statement as mentioned below. If you have any solution to this, do answer. I am trying to make a language model using a ...
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How to find out what each of the layers in NN does?

I have a very simplified view of Neural Networks - you give it input and expected output, and all the rest is a black box. Is it possible to find out, especially in language models, what each layer ...
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1answer
104 views

Feeding XLM-R embeddings to neural machine translation?

I’m very new to the field of deep learning. My aim is to make a translation between Catalan to Catalan Sign Language. The grammar of the two languages is different Input: He sells food. Output (...
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What are the elements in a BERT word embedding?

As far as I understand, BERT is a word embedding that can be fine-tuned or used directly. With older word embeddings (word2vec, Glove), each word was only represented once in the embedding (one ...
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108 views

Cross layer parameter sharing in ALBERT Model

I am reading the paper "ALBERT: LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS". ALBERT uses cross layer parameter sharing to improve the model performance. I don't understand how ...
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What is purpose of the [CLS] token and why its encoding output is important?

I am reading this article on how to use BERT by Jay Alammar and I understand things up until: For sentence classification, we’re only only interested in BERT’s output for the [CLS] token, so we ...
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The differences between BNf and JSGF in NLP?

I wonder what the differences are between the BNF(Backus-Naur Form) and JSGF(Java Speech Grammar Format)? The former is a kind of context-free grammar taught in CS224, but I learned that the JSGF is ...
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Fine tune gpt2 via huggingface API for domain specific LM

i am using the script in the examples folder to fine-tune the LM for a bot meant to deal with insurance related queries. So if someone were to type "i am looking to modify my ..." , the autocomplete ...
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1answer
655 views

How to calculate perplexity in PyTorch?

I am wondering the calculation of perplexity of a language model which is based on ...
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287 views

what are the steps to train BertForMaskedLM model on custom corpus and load it again and test it on new sentences?

what are the steps to train BertForMaskedLM model on custom corpus and load it again and test it on new sentences? I followed the instructions shared in BER github page to train a language model "...
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2answers
494 views

Any good Implementations of Bi-LSTM bahdanau attention in Keras?

From past few weeks I'm trying to learn sequence to sequence machine translation modelling but I couldn't find any good examples/tutorials with bahdanau attention implemented. I did come across a ton ...
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1answer
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Transfer learning between Language Model and classification

Following this fast.ai lecture, I am trying to understand the mechanism of Transfer Learning in NLP from a general Language Model (LM) to a classification problem. What is exactly taken from the ...
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1answer
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BERT Model Evaluation Measure in terms of Syntax Correctness and Semantic Coherence

For example I have an original sentence. The word barking corresponds to the word that is missing. ...
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61 views

Why don't we use BCE(Binary Cross Entropy) for language modeling?

I've seen a lot of RNN/Transformer models use cross entropy loss with softmax. but isn't language modeling a multilabel classification task? what happens if we replace cross entropy loss with binary ...
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1answer
33 views

Language modelling for Spell Checker

I am working on spell checkers, I want to create a spell checker, I am confused about which model to use Word-Level modelling Character-Level modelling plus I am preferring neural networks over ...
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What's the best way to store BERT training data (input IDs)

The tricky thing about the input IDs is what they're varying in length for each data sample, so regular hdf5 may not be ideal. Since Bert is so popular I am wondering if there's an established way to ...
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Skip-gram trained on The Hobbit: no improvement in the similarity of the word representation

I've trained a simple skipgram NNLM (window size = 5) on The Hobbit. This is the rough pseudocode: ...
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1answer
59 views

How to feed data for ngram model?

I want to train an ngram language model Let's say I have the following corpus: ...
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560 views

BERT or ELMo for Document Similarity

Does anyone use BERT or ELMo language models to determine the similarity between two text documents? My question aims to collect all possible ways for combining the contextual word embeddings ...
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1answer
3k views

What is whole word masking in the recent BERT model?

I was checking BERT GitHub page and noticed that there are new models built from a new training technique called "whole word masking". Here is a snippet describing it: In the original pre-...
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1answer
122 views

How should I treat these non-English documents in the NLP task?

So I have a small corpus of about 30k documents and about 50 documents in this corpus are in other languages (Persian, Chinese, Arabic, German, Spanish etc). I will be using this corpus for training a ...
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1answer
74 views

Why Heaps' Law Equation looks so different in this NLP course?

I'm actually not sure if this question is allowed on this community since it's more of a linguistics question than it is a data science question. I've searched extensively on the Web and have failed ...
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27 views

Why is MLP working similar to RNN for text generation

I was trying to perform text generation using only a character level feed-forward neural network after having followed this tutorial which uses LSTM. I one-hot encoded the characters of my corpus ...
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How to prepare the data for text generation task

First, I'm not sure whether the model contains the encoder during training. EOS means end-of-sentence. Encoder and decoder are part of transformer network. If without-encoder, training time: ...
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1answer
39 views

The principle of LM deep model

Language model(LM) is the task of predicting the next word. Does the deep model need the encoder? From the ptb code of tensor2tensor, I find the deep model do not contains the encoder. Or both with-...
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1answer
256 views

What does 'Linear regularities among words' mean?

Context: In the paper "Efficient Estimation of Word Representations in Vector Space" by T. Mikolov et al., the authors make use of the phrase: 'Linear regularities among words'. What does that mean ...
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39 views

How is maximizing L(lambda1, lamda2, lamda3) equivalent to minimizing perplexity?

In language modeling, L(lambda1, lambda2, lambda3) is defined as: Sum(count of trigram(u,v,w) x q(w|u,v)) where u, v, w are words in the corpus and perplexity ...
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Build an Autocomplete model for document titles

I want to build an autocomplete model using RNN where input is article names (documents title). X: ['Billing', 'Loan status', 'Filling loan application', 'Contact Info', ...] The article name can ...
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3answers
4k views

Are there any good out-of-the-box language models for python?

I'm prototyping an application and I need a language model to compute perplexity on some generated sentences. Is there any trained language model in python I can readily use? Something simple like <...
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1answer
91 views

LSTM training/prediction with no starting sequence

ML newbie here. As an exercise, I'm trying to build a character based language model based on a simple 1 layer LSTM. Based on what I've learned about LSTMs, a common usage is to take in a sequence of ...
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1answer
107 views

NLP - extract sentence parts related to people [closed]

Thank you for your help, I appreciate your time.
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1answer
766 views

Fasttext exception error

I'm trying to run language detection using Facebook's fastText through a Python script but I get this error when I load the model : Exception: fastText: Cannot load lid.176.bin due to C++ extension ...
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2answers
20k views

Word2Vec embeddings with TF-IDF

When you train the word2vec model (using for instance, gensim) you supply a list of words/sentences. But there does not seem to be a way to specify weights for the words calculated for instance using ...
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1answer
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Word2Vec, softmax function

I was going term by term through the softmax function for the word2vec (SKIP-GRAM) model. I found most definition of these functions to be not 'clear' so I modified the notation to make sure I ...
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1answer
149 views

How do we pass data to a RNN?

Let's say we have A1, A2, ... , Am different articles in the corpus and each of them has W1, W2, ....., Ww words. We are training a language model on them. Do we: Scheme 1 Take the first batch of ...
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Hidden Markov Models: Linking states to labels after EM training

The tl;dr version first: I have the following problem: I implemented Baum Welch for ergodic HMMs. I do it like this: I pass the model two number C1 and ...
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1answer
201 views

What tools are available for programming language parsing for ML?

I want to preform a machine learning task (e.g. supervised classification, clustering) on a corpus of programming language source code (lets say Python), and I'm looking for tools for parsing and ...
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3answers
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Words to numbers faster lookup

I'm training an LSTM for sentiment analysis on a review dataset downloaded from here. The music review dataset contains about 150K data points (reviews of varying length labelled pos or neg). After ...
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1answer
139 views

Diminishing returns in language identification data set size?

Most problems have a curve whereby the results improve as data are added but level off at some point. Are there research papers or industry results that discuss the correlation between data set size ...
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1answer
315 views

Given one language ngram model, how do I compare likelihoods of two texts of different length?

Let's say I have conditional probabilities estimates for N-grams and I want to find out which of the two sequences of different length 'looks more natural' in terms of the given model. How does one ...
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6answers
27k views

What is the difference between model hyperparameters and model parameters?

I have noticed that such terms as model hyperparameter and model parameter have been used interchangeably on the web without prior clarification. I think this is incorrect and needs explanation. ...