Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use OliverHeine/distilbert-base-uncased_fold_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/distilbert-base-uncased_fold_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/distilbert-base-uncased_fold_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/distilbert-base-uncased_fold_1") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/distilbert-base-uncased_fold_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d6e1b4ec3f664211b9ba697b46f1ca1700fe1a38104f61c8406619af3f5460a
- Size of remote file:
- 5.33 kB
- SHA256:
- a2c136d3371e5b94342ccf08909e7470202547a917c7e73ec49fcca293e74748
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