Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use OliverHeine/distilbert-base-uncased_fold_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/distilbert-base-uncased_fold_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/distilbert-base-uncased_fold_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/distilbert-base-uncased_fold_2") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/distilbert-base-uncased_fold_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eb8fde029b9c9f076f3f004d2aa8b5956406f10774dab7167f4887300def43dd
- Size of remote file:
- 5.33 kB
- SHA256:
- 3d37dd7dd8e5e2fa5237ab4bd08d0454b8070e31e9d6d2addef3c096b9135081
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