Article directory Code display code intent Code interpretation Introduction to knowledge points Parameter calculation of model structure 1. Embedding Layer 2. SimpleRNN Layer 3. Fully connected layer (Dense Layer) 4. The second fully connected layer (Dense Layer) Code display import pandas as pd import tensorflow astf # Build RNN neural network tf.random.set_seed(1) df = pd.read_csv(“../data/Clothing […]
Tag: nlp
Explanation of the principles of RNN in NLP (python example)
Directory code example Code interpretation Introduction to knowledge points Code example import numpy as np import tensorflow astf from tensorflow.keras.layers import SimpleRNNCell # The data to be trained at time t xt = tf.Variable(np.random.randint(2, 3, size=[1, 1]), dtype=tf.float32) print(xt) # https://www.cnblogs.com/Renyi-Fan/p/13722276.html cell = SimpleRNNCell(units=1, activation=None, use_bias=True, kernel_initializer=’ones’, recurrent_initializer=’ones’, bias_initializer=tf.keras.initializers.Constant(value=3)) cell.build(input_shape=[None, 1]) print(‘variables’, cell.variables) print(‘config:’, cell.get_config()) […]
NLP and Knowledge Graph Code Interpretation_Word Embedding
Directory word embedding Simple principle Code examples + interpretation Introduction to professional principles Scenes Word embedding Simple principle Some metaphors and real life examples can be used: Teacher: Do you remember when you were playing with Lego bricks? Each brick represented a specific thing or shape? Now, imagine that each word is like a Lego […]
[NLP] Word copies specified content to a new word document
Table of Contents 1.Complete python code 1.1Open word 1.2Set the starting position 1.3Set the end position 1.4Copy the document content from the starting position to the ending position 1.5Paste the clipboard content and save it to a new word document 1.6Complete python code 2. Results display 2.1 Input 2.2 Output need: Copy the content between […]
EMNLP 2023 ｜ A small tree shakes the tree: Should we perform model editing?
Introduction: Is the field of model editing really trying to hollow out the ocean with a small spoon? This article, drawn from work at Ben-Gurion University in Israel, discusses the problems and concerns of model editors under the current development of LLM. This article was published in EMNLP2023 (Findings). Title: Emptying the Ocean with a […]
NLP Practical BERTopic Topic Analysis
In the field of natural language processing (NLP), topic analysis has always been a hotly discussed topic. Through topic analysis, we can reveal hidden topics in text data, which is very useful for tasks such as information retrieval, text classification, and public opinion analysis. This blog will introduce a topic analysis method based on BERT […]
NLP (71) Further experiments on fine-tuning the RACE dataset for large models
Welcome to follow my public account NLP Fantasy Journey, original technical articles will be pushed out as soon as possible. Welcome to follow my knowledge planet “Natural Language Processing Fantasy Journey“. The author is working hard to build his own technical community. In the article NLP (Seventy) using the LLAMA 2 model to fine-tune Multiple […]
NLP natural language processing – implementation of text information extraction (in-depth syntactic analysis and application)
Blog homepage: I really can’t wake up Series of columns: Deep learning environment construction, environment configuration problem solving, natural language processing, speech signal processing, project development Quotation of the Day: Every step counts, and even if you feel like you are moving slowly, you are still surpassing those who are standing still. Thank you for […]
NLP (Seventy Six) Use large models to complete crossword puzzles
Welcome to follow my public account NLP Fantasy Journey, original technical articles will be pushed out as soon as possible. Welcome to follow my knowledge planet “Natural Language Processing Fantasy Journey“. The author is working hard to build his own technical community. This article explains how to use large models to complete Chinese character crossword […]
NLP (72) uses knowledge distillation to improve model reasoning performance
Welcome to follow my public account NLP Fantasy Journey, original technical articles will be pushed out as soon as possible. Welcome to follow my knowledge planet “Natural Language Processing Fantasy Journey“. The author is working hard to build his own technical community. This article will introduce the model compression method – knowledge distillation. By distilling […]