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:
- 588d2d4c746f2d2fae959e8ccf018a8411da781f32afaa0b28716d17ed8e11ef
- Size of remote file:
- 3.18 kB
- SHA256:
- 7c9d4203b592668f27c73eca9295eccd82fb59579c9906ea027a00ce005b7226
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