Instructions to use notaphoenix/shakespeare_classifier_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use notaphoenix/shakespeare_classifier_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="notaphoenix/shakespeare_classifier_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("notaphoenix/shakespeare_classifier_model") model = AutoModelForSequenceClassification.from_pretrained("notaphoenix/shakespeare_classifier_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ce6b30bfdc826a7443e92d75762113cd0a48f8e60e67008dbdb8ebfe8435f80
- Size of remote file:
- 3.96 kB
- SHA256:
- 51da9768123720e719b56dec37e358d35d458b6104177ebbe39effee1898b755
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