How to Use BERT for Chinese Sentiment Analysis in Python

How to Use BERT for Chinese Sentiment Analysis in Python

In today’s digital age, sentiment analysis is a powerful text analysis tool widely used in market research, public opinion monitoring, customer service, and many other fields. The emergence of the BERT (Bidirectional Encoder Representations from Transformers) model has brought significant breakthroughs to sentiment analysis. Today, let’s delve into how to use BERT for Chinese sentiment … Read more

Why Multi-Agent Systems Fail? Two Interesting Experimental Conclusions on R1 Class Reasoning Model Training and Inference

Why Multi-Agent Systems Fail? Two Interesting Experimental Conclusions on R1 Class Reasoning Model Training and Inference

Today is March 27, 2025, Thursday, Beijing, clear weather. Today, we continue to discuss the R1 reasoning model and the topic of multi-agents. There are three interesting experimental reports. They are: Enhancing LLM Reasoning by Scaling Multi-round Test-time Thinking (Think Twice), Length of Training Data is More Important than Difficulty for Training Reasoning Models, and … Read more

Efficient Transformer for TinyML: Long-Short Distance Attention

Efficient Transformer for TinyML: Long-Short Distance Attention

Click the card below to follow the “LiteAI” public account Hi, everyone, I am Lite. Recently, I shared the Efficient Large Model Full-Stack Technology from Part 1 to 19, including large model quantization, fine-tuning, efficient inference of LLMs, quantum computing, generative AI acceleration, etc. The content links are as follows: Efficient Large Model Full-Stack Technology … Read more

Full-Scale Fine-Tuning Is Harmful!

Full-Scale Fine-Tuning Is Harmful!

MLNLP community is a well-known machine learning and natural language processing community, covering domestic and international NLP master’s and doctoral students, university teachers, and corporate researchers. The Vision of the Community is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning at home and abroad, especially … Read more

ICML 2024: New Fourier Fine-Tuning Method Reduces Parameters

ICML 2024: New Fourier Fine-Tuning Method Reduces Parameters

This article introducesThe Hong Kong University of Science and Technology (Guangzhou)a paper on efficient fine-tuning of large models (LLM PEFT Fine-tuning) titled “Parameter-Efficient Fine-Tuning with Discrete Fourier Transform”, which has been accepted by ICML 2024, and the code has been open-sourced. Paper link: https://arxiv.org/abs/2405.03003 Project link: https://github.com/Chaos96/fourierft Background Large foundation models have achieved remarkable successes … Read more

Integrating MoE into LoRA: The Birth of an Article

Integrating MoE into LoRA: The Birth of an Article

MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering audiences including NLP graduate students, university teachers, and industry researchers. The vision of the community is to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning, especially for beginners. Source … Read more

Cost-Effective Fine-Tuning with LoRA for Large Models

Cost-Effective Fine-Tuning with LoRA for Large Models

MLNLP community is a well-known machine learning and natural language processing community at home and abroad, covering domestic and international NLP graduate students, university teachers, and corporate researchers. The vision of the community is to promote communication and progress between academia, industry, and enthusiasts in natural language processing and machine learning, especially for beginners. Selected … Read more

Implementing LoRA From Scratch with Practical Tips

Implementing LoRA From Scratch with Practical Tips

Source: DeepHub IMBA This article is approximately 5000 words long and is suggested to be read in 10 minutes. This article starts with a simple implementation of LoRA, delving into LoRA, its practical implementation, and benchmarking. LoRA stands for Low-Rank Adaptation, which provides an efficient and lightweight method for fine-tuning pre-existing language models. One of … Read more

Differences Between LoRA and Full Fine-Tuning Explained in MIT Paper

Differences Between LoRA and Full Fine-Tuning Explained in MIT Paper

MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP graduate students, university teachers, and corporate researchers. The vision of the community is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning, especially for beginners. Reprinted from | … Read more

AI Agents Pioneer CAMEL: The First Large Model Multi-Agent Framework

AI Agents Pioneer CAMEL: The First Large Model Multi-Agent Framework

MLNLP community is a well-known machine learning and natural language processing community at home and abroad, covering domestic and foreign NLP master’s and doctoral students, university teachers, and enterprise researchers. The vision of the community is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning at … Read more