Text Classification
Transformers
TensorFlow
bert
generated_from_keras_callback
text-embeddings-inference
Instructions to use cruiser/bert_model_kaggle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cruiser/bert_model_kaggle with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cruiser/bert_model_kaggle")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cruiser/bert_model_kaggle") model = AutoModelForSequenceClassification.from_pretrained("cruiser/bert_model_kaggle", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b29f509399418662e95e28f0e1c824d879fa64ed45009761659e0a2e443c413
- Size of remote file:
- 438 MB
- SHA256:
- 72f957dfe30f25b9e697e56998506979e1070d95017b894ab1aaf6aafdd27d33
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