| {} | |
| ### 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 | |
| model_name = "interneuronai/advertisement_cap_on_banner_classification_bert" | |
| 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)) |