Click the Card below and follow the “CVer” public account AI/CV heavy-duty information, delivered as soon as possible Click to enter->[Computer Vision and Transformer] Communication Group Reprinted from: Xinzhiyuan | Editor: Run So sleepy [Introduction]Recently, researchers from the Australian National University, Oxford and Chiyuan have proposed an agent framework driven by LLM that can generate […]
Tag: sentence
Word2vec (CBOW, Skip-gram) word vector training based on sentencepiece tool and unicode encoding word segmentation, combined with TextCNN model, replaces the initial word vector for text classification tasks
Word2vec (CBOW, Skip-gram) word vector training based on sentencepiece tool and unicode encoding word segmentation, combined with TextCNN model, replacing the initial word vector for text classification tasks The experiment done by the blogger this time is difficult, but the idea is very good. I think those with poor foundation may not understand my question. […]
SentenceTransformer accelerates vectorization using multiple GPUs
Article directory Preface code Foreword When we need to vectorize large-scale data to store it in a vector database, and there are multiple GPUs at our disposal on the server, we hope to use all GPUs at the same time to parallelize the process and accelerate the vectorization. Code Just a few lines of code, […]
BPE, WordPiece and SentencePiece
BPE, WordPiece and SentencePiece Jarkata focuses on IP jurisdiction: Shanghai 0.4252022.04.25 10:59:56 Word Count 2,726 Reading 10,692 1. Background and foundation When using the GPT BERT model to input words, tokenization is often performed first. What are the specific goals and granularity of tokenize? Tokenize also has many categories, advantages and disadvantages. This article summarizes […]
SentencePiece, an essential tool for large model vocabulary expansion
SentencePiece, an essential tool for large model vocabulary expansion Original Eat jelly without spitting out jelly skin Eat jelly without spitting out jelly skin 2023-08-20 09:42 included in collection #Large model 56 #AI9 Background As ChatGPT quickly emerges from the scene, large open source models have also blossomed in recent months. Currently, there are three […]
[Multiple target tracking] TrackFormer took three days to translate a single sentence! ! !
[Multiple target tracking] TrackFormer took three days to translate a single sentence! ! ! TrackFormer: Multi-Object Tracking with Transformers Abstract The challenging task of multi-object tracking (MOT) re-quires simultaneous reasoning about track initialization, identity, and spatio-temporal trajectories. We formulate this task as a frame-to-frame set prediction problem andintroduce TrackFormer, an end- to-end trainable MOT ap-proach […]
Big Language Model 10 SentencePiece
Tokenizer Large language models such as GPT-3/4 and LlaMA/LlaMA2 all use tokens as the input and output of the model. The input is text, and then the text is converted into a token (positive integer), and then from a string of tokens (corresponding to the text) Predict the next token. Enter the tokenizer provided by […]
Python, Bytetrack source code interpretation, parameters, source code explanation, code analysis sentence by sentence, target tracking
Article directory 1. Get the index 2. High-scoring boxes participate in matching, and there may be boxes left that cannot be matched. 3. Low score boxes participate in matching 4. Handle unconfirmed matches 5. Create a new [STrack object] 6. Throw away [STrack objects] that have not been matched to the frame for too long […]
Unsupervised Text Summarization Using Sentence Embeddings
1. Description This is a homework exercise for an AI graduate class, In this article, I will describe the method I used to perform text summarization in Python, which was one of the cool to-do lists assigned to me by my mentor. 2. What is a text summary? Text summarization is the process of extracting […]
Pre-trained ernie model fine-tuning sentence classification practice
1. Preparation of data set First prepare our own data set, I asked chatgpt to help generate some { “title”:”Zun Du Fake Du”, “data”: [{“text”: “I love black silk beauties”,”labels”: 2}, {“text”: “I love white silk beauty”,”labels”: 1}, {“text”: “Black silk beauty is really sexy”,”labels”: 2}, {“text”: “White silk beauty is also very charming”,”labels”: 1}, […]