Instructions to use choiruzzia/best_berita_bert_model_fold_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use choiruzzia/best_berita_bert_model_fold_5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="choiruzzia/best_berita_bert_model_fold_5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("choiruzzia/best_berita_bert_model_fold_5") model = AutoModelForSequenceClassification.from_pretrained("choiruzzia/best_berita_bert_model_fold_5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- baf9f64453babab0df99b4614cef96770fd87b972d849d877537fea2fdd47a4f
- Size of remote file:
- 443 MB
- SHA256:
- 3e0a4138c9c6279facbac1873acef0c55541a22d547a2fb797239133c7b2cb3c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.