Questions tagged [fasttext]
The fasttext tag has no usage guidance.
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How does FastText create n-gram word features?
In the paper Bag of Tricks for Efficient Text Classification they talk about creating n-gram (word) features, and in their experiments they show results for both 1-gram and bi-gram.
As far as I ...
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Finetuning fasttext with unlabeled text corpus
I am training a classifier which is supposed to take the name of a product as input. For this purpose I want to finetune a pre-existing fasttext model on my article names.
My code looks like this
<...
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Encountered a problem while installing [ FastText ] library on MacOS
I have been trying to install the "FastText" library on macOS but I keep encountering a Runtime error.
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How to fine-tune hyperameters of unsupervised training in fasttext?
I want train fasttext unsupervised model on my text dataset. However there are many hyperparameters in train_unsupervised method:
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Is it normal for a model to perform worse with the use of word embeddings?
I have a multiclass text classification problem and I've tried different solutions and models, but I was not satisfied with the results.
So I've decided to use GloVe ( Global Vectors for Word ...
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Should I use Pad Sequence when using Word Vectors?
I have an unbalanced text data set. I want to use word vectors to embed words. When I use pad sequence? Before or after the word vector? I tried it, after the word vector I used pad sequence but my ...
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Training fasttext on your own corpus
I want to train fasttext on my own corpus. However, I have a small question before continuing. Do I need each sentences as a different item in corpus or can I have many sentences as one item?
For ...
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Data Set and guidance for Occupations/ Roles classification problem
I am working on a project where I need to find similar roles -- for example, Software Engineer, Soft. Engineer , Software Eng ( all should be marked similar)
Currently, I have tried using the Standard ...
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When are subword ngrams trained in fasttext? (Enriching Word Vectors with Subword Information)
when is the training for subword ngrams done? is it done simultaneously as when the word representation are trained? or is it done at the end, after word representations are created?
fasttext ...
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Pre-trained models for finding similar word n-grams
Are there any pre-trained models for finding similar word n-grams, where n>1?
FastText, for instance, seems to work only on unigrams:
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Initializing weights that are a pointwise product of multiple variables
In two-layer perceptrons that slide across words of text, such as word2vec and fastText, hidden layer heights may be a product of two random variables such as positional embeddings and word embeddings ...
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Explain FastText model using SHAP values
I have trained fastText model and some fully connected network build on its embeddings. I figured out how to use Lime on it: complete example can be found in Natural Language Processing Is Fun Part 3: ...
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Extracting vectors of FastText own model to use it on a NN
I have trained my own model of fasttext using the pretrained model of English available on their website with the next code:
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FastText Model Explained
I was reading the FastText paper and I have a few questions about the model used for classification. Since I am not from NLP background, some I am unfamiliar with the jargon.
In the figure, what ...
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Removing duplicate records before training
I am currently working on a project classifying text into classes. The specific problem is classifying job titles into various industry codes. For example "McDonalds Employee" might get classified to ...
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