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README.md
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---
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{}
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---
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### Advertisement Cap on Banner Classification
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**Description:** Automatically classify and assign appropriate advertisement cap to banners to streamline manufacturing and delivery processes.
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## How to Use
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Here is how to use this model to classify text into different categories:
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from transformers import AutoModelForSequenceClassification, AutoTokenizer
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model_name = "interneuronai/advertisement_cap_on_banner_classification_bert"
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model = AutoModelForSequenceClassification.from_pretrained(model_name)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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def classify_text(text):
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inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512)
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outputs = model(**inputs)
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predictions = outputs.logits.argmax(-1)
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return predictions.item()
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text = "Your text here"
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print("Category:", classify_text(text))
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