Instructions to use OliverHeine/bert-base-uncased_fold_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/bert-base-uncased_fold_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/bert-base-uncased_fold_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/bert-base-uncased_fold_3") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/bert-base-uncased_fold_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea3d0134b8108f63f514b0c146afa526f62cd10632cb0ce83100c2c3b25249f1
- Size of remote file:
- 5.27 kB
- SHA256:
- 6160d4135fe89d1aa410cfb7c1bc90591663750fe8f5dff40f2bb939819c8d7b
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