interneuronai/company_sentiment_analysis_bart_dataset
Company_Sentiment_Analysis Description: Analyze customer opinions, feedback, and reviews about the company software, websites, and IT services to gain insights and improve products and services How to Use Here is how to use this model to classify text into different categories: from transformers import AutoModelForSequenceClassification, AutoTokenizer model_name = "interneuronai/company_sentiment_analysis_bart" model =… See the full description on the dataset page: https://huggingface.co/datasets/interneuronai/company_sentiment_analysis_bart_dataset.
CompanySentimentAnalysis
Description: Analyze customer opinions, feedback, and reviews about the company software, websites, and IT services to gain insights and improve products and services
How to Use
Here is how to use this model to classify text into different categories:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
modelname = "interneuronai/companysentimentanalysisbart" model = AutoModelForSequenceClassification.frompretrained(modelname) tokenizer = AutoTokenizer.frompretrained(modelname)
def classifytext(text): inputs = tokenizer(text, returntensors="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))