Instructions to use tejasc/AdTypeClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tejasc/AdTypeClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tejasc/AdTypeClassifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tejasc/AdTypeClassifier") model = AutoModelForSequenceClassification.from_pretrained("tejasc/AdTypeClassifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Card for Model ID
You can use this classifier on Google Ads to determine which of the 5 types of Ad promotions a Google Ad pertains to.
Label Mappings
- LABEL_0: product promotion
- LABEL_1: service promotion
- LABEL_2: sales promotion
- LABEL_3: lead generation
- LABEL_4: brand awareness
Model Description
This classifier is a trained checkpoint of Bert, specifically bert-base-uncased, trained on 10,000 Google Ad inputs. These ads were scraped, cleaned, and labeled using OpenAi 3.5 turbo.
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