Programming VIP

reference resources: CRF++: Yet Another CRF toolkitCRF + + usage: Chinese TranslationModel DownloadModel installation and training   train Mode 1: % crf_learn template_file train_file model_file Where template_file and train_file files that need to be prepared in advance. crf_learn in model_file to generate the trained model file. The tra ...

catalogue 1, Basic process of text generation and Translation Training and decoding of translation models Training process Decoding process Training and decoding of generation class model (GPT Series) Training process Decoding process 2, Decoding strategy 1. Greedy search 2,beam_search cluster search 3. Random sampling 4. Top-K Samp ...

Emotion analysis competition: score 0.7943 Here, the high-level API of the propeller is used to quickly build a model to submit the results of the emotion analysis competition. Please refer to the specific principle and analysis NLP punch in camp practice lesson 5: text emotion analysis . The following will be divided into three parts: sent ...

1, Stacked RNN from keras.models import Sequential from keras.layers import LSTM,Embedding,Dense # Set super parameters vocabulary = 10000 # There are 10000 words in the dictionary embedding_dim=32 # shape(x)=32, and the dimension of word vector x is 32 word_num = 500 # Each film review has 500 words. If it exceeds 500 words ...

preface 1. This article is based on the previous article: Some optimizations on improving the accuracy of OCR recognition (2) Some optimizations are made to improve the accuracy of picture direction recognition to 96%. 2. Before reading this article, it is recommended to read the previous one for better understanding 1, Optimization ide ...

In many problems, obtaining a large amount of accurate data needs a high cost, which often limits the application of deep learning. Active learning can use a small amount of labeled data to achieve high learning accuracy by filtering the unlabeled data. This paper will provide code implementation, show experimental results and some thoughts. C ...

Code Intelligence: Problems and Solutions Today, the natural language processing revolution is triggered by the large model based on pre training, and the code intelligence technology is also developing rapidly. So, what is code intelligence doing? Maybe many students will have more science fiction ideas, such as programmers going to lose thei ...

Probabilistic representation of CBOW model: P(A): probability of occurrence of A. P(A,B): the probability of simultaneous occurrence of event A and event B, which is called joint probability. P(A|B): the probability of event A after giving the information of event B, which is called A posteriori probability. CBOW model: the probability of o ...

1, Introduction to LDA theme model LDA topic model is mainly used to infer the topic distribution of documents. The topic of each document in the document set can be given in the form of probability distribution, and topic clustering or text classification can be carried out according to the topic. LDA topic model does not care about the orde ...

  🚀 The principle analysis of BERT can be seen as follows: Bert: pre training of deep bidirectional transformers for language understanding   🚀 The code implementation mainly uses huggingface's transformers Library (4.9.1) and torch Library (1.6.0) pip install transformers pip install torch 🚀 Let's talk about my approach fi ...