Text Classification
Transformers
TensorFlow
TensorBoard
Safetensors
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use PDAP/url-relevance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PDAP/url-relevance with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PDAP/url-relevance")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PDAP/url-relevance") model = AutoModelForSequenceClassification.from_pretrained("PDAP/url-relevance", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload 2 files
Browse files- model.safetensors +2 -2
- tf_model.h5 +3 -0
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