Instructions to use date3k2/gpt2-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use date3k2/gpt2-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="date3k2/gpt2-text-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("date3k2/gpt2-text-classification") model = AutoModelForSequenceClassification.from_pretrained("date3k2/gpt2-text-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 06f6b792c6da060e64f48d3131dc6ac7712e3cab2ad82ce816f05d626d0da775
- Size of remote file:
- 5.11 kB
- SHA256:
- 2002da6f8c183b28f0168cffc45471042326d862dbcc839e8ea6018431ce1e36
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