Questions tagged [language-model]

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19 views

Optimal input setup for character-level text classification RNN

I want to classify 500-character long text samples as to whether they look like natural language using a character-level RNN. I'm unsure as to the best way to feed the input to the RNN. Here are two ...
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8 views

Help understanding input to biaxial network for generating music

I am reading Composing Music With Recurrent Neural Networks by Daniel D. Johnson. But I am really confused about the input passed to this network. If we pass notes of music along the time axis, then ...
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1answer
19 views

From where does BERT get the tokens it predicts?

When BERT is used for masked language modeling, it masks a token and then tries to predict it. What are the candidate tokens BERT can choose from? Does it just predict an integer (like a regression ...
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1answer
22 views

What is the difference between GPT blocks and Transformer Decoder blocks?

I know GPT is a Transformer-based Neural Network, composed of several blocks. These blocks are based on the original Transformer's Decoder blocks, but are they exactly the same? In the original ...
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1answer
23 views

Can I fine-tune the BERT on a dissimilar/unrelated task?

In the original BERT paper, section 3 (arXiv:1810.04805) it is mentioned: "During pre-training, the model is trained on unlabeled data over different pre-training tasks." I am not sure if I ...
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44 views

For an n-Gram model with n>2, do we need more context at end of each sentence?

Jurafsky's book says we need to add context to left and right of a sentence: Does this mean, for example, if we've a corpus of three sentences: ...
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1answer
83 views

In smoothing of n-gram model in NLP, why don't we consider start and end of sentence tokens?

When learning Add-1 smoothing, I found that somehow we're adding 1 to each word in our vocabulary but not considering start-of-sentence and end-of-sentence as two words in the vocabulary. Let me throw ...
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2answers
49 views

Evaluating Language Model on specific topic

I have finetuned a pretrained Language Model(GPT-2) on a custom dataset of mine. I would like a way of evaluating the ability of my model to generate sentences of a specific predefined topic, given in ...
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9 views

How to: Plot global mean precipitation data from the NDAA onto map regions?

Wondering how to/ if I can display amount of rainfall across regions (in env variable) on the map areas so that the points only pertain to separate languages and sized by rainsetPropn. Have used data ...
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1answer
22 views

State-of-the-art Python packages that can evaluate language similarity

I am trying to evaluate the likelihood of generating a specific sentence out of a large set of sentences. To do this, I start from a simple approach: training a custom n-gram language model and ...
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0answers
20 views

When using padding in sequence models, is Keras validation accuracy valid/ reliable?

I have a group of non zero sequences with different lengths and I am using Keras LSTM to model these sequences. I use Keras Tokenizer to tokenize (tokens start from 1). In order to make sequences have ...
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0answers
11 views

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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1answer
86 views
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11 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
25 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
429 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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1answer
35 views

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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0answers
11 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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41 views

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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16 views

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
189 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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2answers
998 views

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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156 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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2answers
4k views

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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52 views

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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101 views

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
943 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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0answers
413 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
802 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
41 views

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
121 views

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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1answer
50 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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0answers
16 views

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
96 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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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
187 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
111 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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0answers
29 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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0answers
34 views

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
40 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
315 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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0answers
58 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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0answers
74 views

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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4answers
5k 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
101 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
113 views

NLP - extract sentence parts related to people [closed]

Thank you for your help, I appreciate your time.
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1answer
877 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
22k 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
2k views

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 ...
4
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1answer
152 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 ...