Instructions to use OliverHeine/bert-base-uncased_train_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/bert-base-uncased_train_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/bert-base-uncased_train_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/bert-base-uncased_train_v1") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/bert-base-uncased_train_v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a49e7f8eb38ccb584e67c4a58d304d15629f82f68de67419618a30a169298c68
- Size of remote file:
- 5.27 kB
- SHA256:
- 10eeb8d4874f65f4a60991ec0eb1d5e068d615c60c7d5a345d164d099477977e
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