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
- Xet hash:
- cfa0143788cded3964e310ba7337193093075afd34545ea2fcafd6a5ef43894b
- Size of remote file:
- 433 MB
- SHA256:
- fef77460d50986fd33f051dd5162d89dd34cd6ea8c382a36fec90ed2bf0a47f0
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