Text Classification
Transformers
TensorFlow
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use cruiser/distilbert_model_kaggle_200_epoch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cruiser/distilbert_model_kaggle_200_epoch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cruiser/distilbert_model_kaggle_200_epoch")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cruiser/distilbert_model_kaggle_200_epoch") model = AutoModelForSequenceClassification.from_pretrained("cruiser/distilbert_model_kaggle_200_epoch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d97bab35a1ec98c10a3ebe882a83aca60e18932a72f7a0386b39005ba48c0457
- Size of remote file:
- 268 MB
- SHA256:
- dc1955f6679608a7f44c2524550253d4229b979169bd06d9e1b427963a0f10ac
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