NJUxlj/bert-gpt2-ecommerce-review-ner
基于Bert+MoE+Qwen2拼接后的模型和LoRA微调的电商评论NER模型。使用transformers+deepspeed进行训练，swanlab进行监控。
This project helps e-commerce businesses automatically identify and extract key product-related information from customer reviews. It takes raw customer reviews as input and outputs structured data, highlighting entities like product names, brands, models, and other relevant terms. This allows product managers, marketing analysts, and customer service teams to quickly understand customer sentiment and product feedback.
No commits in the last 6 months.
Use this if you need to automatically extract specific pieces of information, such as product names or brands, from a large volume of e-commerce customer reviews.
Not ideal if your primary goal is to analyze general sentiment or topics in reviews, rather than extracting specific named entities.
Stars
7
Forks
—
Language
Python
License
—
Category
Last pushed
Apr 01, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/NJUxlj/bert-gpt2-ecommerce-review-ner"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
ScalaConsultants/Aspect-Based-Sentiment-Analysis
💭 Aspect-Based-Sentiment-Analysis: Transformer & Explainable ML (TensorFlow)
curiousily/Deploy-BERT-for-Sentiment-Analysis-with-FastAPI
Deploy BERT for Sentiment Analysis as REST API using FastAPI, Transformers by Hugging Face and PyTorch
cleopatra-itn/fair_multimodal_sentiment
Code and Splits for the paper "A Fair and Comprehensive Comparison of Multimodal Tweet Sentiment...
mohd-faizy/06P_Sentiment-Analysis-With-Deep-Learning-Using-BERT
Finetuning BERT in PyTorch for sentiment analysis.
sampathkethineedi/bert-topic-sentiment
Topic Based Sentiment Detection using BERT