interneuronai/classifying_member_activity_levels_distilbert

Classifying Member Activity Levels

Description: Categorize members based on their activity levels, such as low, medium, and high, to enable tailored engagement and retention strategies.

How to Use

Here is how to use this model to classify text into different categories:

    from transformers import AutoModelForSequenceClassification, AutoTokenizer
    
    model_name = "interneuronai/classifying_member_activity_levels_distilbert"
    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))