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
- Xet hash:
- 4a3cac19b85fb88a13c06a67de9603f80495e5aded001fc428ad620a4dcf3250
- Size of remote file:
- 438 MB
- SHA256:
- 4119cac55c3a7632a2584a1671ff81edcbe0e9f49b43ea9269276fb33ba1459a
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