| {} | |
| ### Gym Membership Upgrades | |
| **Description:** Classify member feedback to identify potential areas of improvement and opportunities for upselling premium services, such as personal training or nutrition counseling. | |
| ## How to Use | |
| Here is how to use this model to classify text into different categories: | |
| from transformers import AutoModelForSequenceClassification, AutoTokenizer | |
| model_name = "interneuronai/gym_membership_upgrades_pegasus" | |
| 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)) |