{} | |
### 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)) |