interneuronai/customer_feedback_analysis_-_company_x_bart_dataset

--- {} --- ### Customer Feedback Analysis - Company X **Description:** Classify customer feedback based on sentiment, topic, and urgency. Prioritize and address customer concerns, improve products and services, and enhance customer satisfaction. ## How to Use Here is how to use this model to classify text into different categories: from transformers import AutoModelForSequenceClassification, AutoTokenizer model_name = "interneuronai/customer_feedback_analysis_-_company_x_bart" model = AutoModelForSequenceClassification.from_pretrained(model_name) tokenizer = AutoTokenizer.from_pretrained(model_name) def classify_text(text): inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512) outputs = model(**inputs) predictions = outputs.logits.argmax(-1) return predictions.item() text = "Your text here" print("Category:", classify_text(text))

原始信息汇总

数据集概述

数据集名称

• Customer Feedback Analysis - Company X

数据集描述

• 该数据集用于根据情感、主题和紧急程度对客户反馈进行分类。目的是优先处理和解决客户关注的问题，改进产品和服务，提升客户满意度。

使用方法

• 使用该数据集需要从transformers库中导入AutoModelForSequenceClassification和AutoTokenizer。
• 模型和标记器的名称是interneuronai/customer_feedback_analysis_-_company_x_bart。
• 通过定义classify_text函数来分类文本，该函数接受文本输入，使用标记器处理文本，然后通过模型进行预测，返回预测的类别。
• 示例代码展示了如何使用该函数对输入文本进行分类。