File size: 976 Bytes
b45ab74
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
---
{}
---
### 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))