Instructions to use twn39/roc-bert-base-zh-finetune-dianping with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use twn39/roc-bert-base-zh-finetune-dianping with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="twn39/roc-bert-base-zh-finetune-dianping")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("twn39/roc-bert-base-zh-finetune-dianping") model = AutoModelForSequenceClassification.from_pretrained("twn39/roc-bert-base-zh-finetune-dianping", device_map="auto") - Notebooks
- Google Colab
- Kaggle
最终评估结果: {'eval_loss': 0.6359742283821106, 'eval_accuracy': 0.7420646692376149, 'eval_runtime': 40.543, 'eval_samples_per_second': 166.292, 'eval_steps_per_second': 10.409, 'epoch': 3.0}
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Model tree for twn39/roc-bert-base-zh-finetune-dianping
Base model
weiweishi/roc-bert-base-zh