interneuronai/advertisement_cap_on_banner_classification_bert

Advertisement Cap on Banner Classification

Description: Automatically classify and assign appropriate advertisement cap to banners to streamline manufacturing and delivery processes.

How to Use

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

from transformers import AutoModelForSequenceClassification, AutoTokenizer

modelname = "interneuronai/advertisementcaponbannerclassificationbert" 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))