Instructions to use OliverHeine/bert-base-uncased_fold_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/bert-base-uncased_fold_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/bert-base-uncased_fold_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/bert-base-uncased_fold_1") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/bert-base-uncased_fold_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc7d64342339fb1c48d1b1eb2ed61040c86783d0c0d996bbc24f8197670a2377
- Size of remote file:
- 5.27 kB
- SHA256:
- fba518a55c93e50eabcdb1243e37070364e696e39841ab6026e0f1f6c74e007b
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