Instructions to use cungnlp/FineTuningBERTbaseClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cungnlp/FineTuningBERTbaseClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cungnlp/FineTuningBERTbaseClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cungnlp/FineTuningBERTbaseClassification") model = AutoModelForSequenceClassification.from_pretrained("cungnlp/FineTuningBERTbaseClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse filesEnglish sentence classification model
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labels meaning
0 Positive
1 Negative
2 Neutral
3 Extremely Positive
4 Extremely Negative