Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use OliverHeine/distilbert-base-uncased_fold_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/distilbert-base-uncased_fold_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/distilbert-base-uncased_fold_4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/distilbert-base-uncased_fold_4") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/distilbert-base-uncased_fold_4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3367e429333f0f9e1b41772a8c44f24aa69cfea9e645743c24a6989b0fa278bf
- Size of remote file:
- 5.33 kB
- SHA256:
- 4e8a30b4f32013ba4d604a91f504d82cfa346752a36433fda80f907bb92dcd0b
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