Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Sharpaxis/distilbert-news-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sharpaxis/distilbert-news-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sharpaxis/distilbert-news-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sharpaxis/distilbert-news-classification") model = AutoModelForSequenceClassification.from_pretrained("Sharpaxis/distilbert-news-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8c6ba660662a5bd53ba42b9285e3c395c48fc72c96a0bd2bf6149db33305258
- Size of remote file:
- 5.37 kB
- SHA256:
- 7a205b65b61a3e0407a7f9b6211fd70c6379ba157804599b177c5cc01b76fcce
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.