Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Sharpaxis/NEWS_BERT_FINETUNED with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sharpaxis/NEWS_BERT_FINETUNED with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sharpaxis/NEWS_BERT_FINETUNED")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sharpaxis/NEWS_BERT_FINETUNED") model = AutoModelForSequenceClassification.from_pretrained("Sharpaxis/NEWS_BERT_FINETUNED", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 780317d5639e7416be289ac855ce8c1a3d16e4866064146f8e08578d848cf504
- Size of remote file:
- 5.24 kB
- SHA256:
- 11f39b783a589ae4cf29b0187e6fb7e35d5901cc777eb94ceef65a82fe07a1de
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