Instructions to use adit94/relevancy_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adit94/relevancy_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="adit94/relevancy_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("adit94/relevancy_classifier") model = AutoModelForSequenceClassification.from_pretrained("adit94/relevancy_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bf793b2e9db85364977aab6d848514599eda1ac1dc07c11f9b21069ba6abb56
- Size of remote file:
- 536 MB
- SHA256:
- 56122ccaace8a2b3138755053079b668fd3b1c1fbc48d5dbbf58b623f4651176
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