NLP中的经典:BERT和ALBERT,ALBERT模型V2 感觉来了 NLP(二):n元模型 一. 语言建模(Language Modeling) s1 = 我刚吃过 早饭 s2 = 刚我过 早饭 吃 对于上面这两句话,很明显,s1读起来要比s2通顺的多,也就是说P(s1) > P(s2);对于由n个词构成的不同句… 月臻发表于机器/深度... NLP(二)N-gram...
assert type(word) == str return self.words_dict[word] if word in self.words_dict else self.words_dict["<unk>"] def id_to_word(self, idx): assert type(idx) == int return self.index_dict[idx] if idx in self.index_dict else "<unk>" def __len__(self): return len(self.words...
Unregularised mLSTM (Krause et al., 2016) 1.40 45M Multiplicative LSTM for sequence modelling Official Penn Treebank The vocabulary of the words in the character-level dataset is limited to 10 000 - the same vocabulary as used in the word level dataset. This vastly simplifies the task of...
Language Modelling and RNNs Part 2 - Phil Blunsom(中) https://www.youtube.com/playlist?list=PL613dYIGMXoZBtZhbyiBqb0QtgK6oJbpm 牛津大学与DeepMind合办的深度学习自然语言处理课程,GitHub:https://github.com/oxford-cs-deepnlp-2017/lectures
One area that has seen remarkable growth in recent times is language modelling, a statistical technique to compute the probability of tokens or words in a given sentence. In this paper, we attempt to present an overview of various representations with respect to language modelling, from neural ...
deep-learningtext-generationpytorchneural-networkscomputational-linguisticslanguage-modellingrnns UpdatedJun 23, 2020 Python bjam24/agh-natural-language-processing Star1 This respository contains projects made for the NLP course at the AGH UST in 2024/2025. Obtained maximum grade 5.0. ...
Many Natural Language Processing can be structured as (conditional) language modelling. Such as Translation: P(certain Chinese text | given English text) Note that the Prob follows the Bayes Formula. How to evaluate a Language Model? Measured with cross entropy. ...
2. Frederic Morin, Yoshua Bengio. Hierarchical Probabilistic Neural Network Language Model. Innovations in Machine Learning(2006). 2006.提出了Hierarchical NPLM 3. Andriy Mnih, Geoffrey Hinton. Three New Graphical Models for Statistical Language Modelling. ICML(2007). 2007. 提出了三个Model,其中提的较...
Transformers for Information Retrieval, Text Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI - ThilinaRajapakse/simpletransformers
In 2019, there was a big boost in the popularity of Language Modelling thanks to the development of transformers like BERT, GPT-2, and XLM. These transformer-based models can be adapted from a general-purpose language model to a specific downstream task which is known as fine-tuning. The ...