Instructions to use choiruzzia/best_berita_roberta_model_fold_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use choiruzzia/best_berita_roberta_model_fold_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="choiruzzia/best_berita_roberta_model_fold_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("choiruzzia/best_berita_roberta_model_fold_3") model = AutoModelForSequenceClassification.from_pretrained("choiruzzia/best_berita_roberta_model_fold_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c221b81a5bc2e881dd85dfb4bd5942e8319acbd0a65a3c08e39c5ba571beed53
- Size of remote file:
- 5.18 kB
- SHA256:
- f94e102af3943a55371a82e74a25af38fe29a25538d608e98d659ca1c614319d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.