interneuronai/gym_membership_upgrades_pegasus_dataset
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 =… See the full description on the dataset page: https://huggingface.co/datasets/interneuronai/gym_membership_upgrades_pegasus_dataset.
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
modelname = "interneuronai/gymmembershipupgradespegasus" 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))