Instructions to use TuringGame/gpt2-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TuringGame/gpt2-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TuringGame/gpt2-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TuringGame/gpt2-classifier") model = AutoModelForSequenceClassification.from_pretrained("TuringGame/gpt2-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85280cc91e814ad3d8ce61558147d2563633b2d76b0d50aa2a1334a7073b5c9b
- Size of remote file:
- 498 MB
- SHA256:
- d4d51e9a8234810f10418262ebbc7c9f177f1971bece866672d77ead18995b6a
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