Instructions to use goldandrabbit/finetune_bert_using_Trainer_vs_pytorch_train_loop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use goldandrabbit/finetune_bert_using_Trainer_vs_pytorch_train_loop with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="goldandrabbit/finetune_bert_using_Trainer_vs_pytorch_train_loop")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("goldandrabbit/finetune_bert_using_Trainer_vs_pytorch_train_loop") model = AutoModelForSequenceClassification.from_pretrained("goldandrabbit/finetune_bert_using_Trainer_vs_pytorch_train_loop") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d88b98e69d7291968ef3d9bcf891d0a74fc314da086a80390d8d07e74a4d00cf
- Size of remote file:
- 433 MB
- SHA256:
- 88a4a780f11e73d8172eae5936d0921cef2bd1a0aa1762a770eb8a44036024ce
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