Edit model card

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)) 
Downloads last month
10
Safetensors
Model size
612M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.