Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Sharpaxis/News_classification_distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sharpaxis/News_classification_distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sharpaxis/News_classification_distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sharpaxis/News_classification_distilbert") model = AutoModelForSequenceClassification.from_pretrained("Sharpaxis/News_classification_distilbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5cd45f2c21af0d222b5fad1bd3c8a1213707baca2926662f4af3ca480c6db6b8
- Size of remote file:
- 268 MB
- SHA256:
- 833087bbdda05da41cb99ecfb1c55805cb8a7d784cd1cf58fe0e6b5e3c384ae2
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