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:
- 5b4ff9d23973f264836c34337d4180988f6b8e10edb36398b70e1bc3663f964b
- Size of remote file:
- 268 MB
- SHA256:
- 585eeafc164ae4613b202e04569e626a9aa101224a41e4eca7d3a4322afb263f
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