Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use OliverHeine/distilbert-base-uncased_fold_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/distilbert-base-uncased_fold_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/distilbert-base-uncased_fold_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/distilbert-base-uncased_fold_3") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/distilbert-base-uncased_fold_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ef701e4f3bf5785edb252cf5a3123a666bf3239ceb1fb6687202d6eae7423d7
- Size of remote file:
- 5.33 kB
- SHA256:
- d2f32e41e9285104f077c008223f2236830c633c3628a39213601c510a965d9e
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