Instructions to use OliverHeine/bert-base-uncased_fold_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/bert-base-uncased_fold_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/bert-base-uncased_fold_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/bert-base-uncased_fold_2") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/bert-base-uncased_fold_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1994dc6daf9ab165dc694a5424fc1160a81d12d75dc0a29940524c9298b8f2cb
- Size of remote file:
- 5.27 kB
- SHA256:
- cebb8281ac33668b92aa964249f20495855caa3285b021940677211417560e73
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