Instructions to use simonmun/HSC_gpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonmun/HSC_gpt2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="simonmun/HSC_gpt2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("simonmun/HSC_gpt2") model = AutoModelForSequenceClassification.from_pretrained("simonmun/HSC_gpt2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3c727d2709976083cec8c2e7daac58aeb7d4576875a0da53775c0d2340c483a
- Size of remote file:
- 498 MB
- SHA256:
- b3013559257026fc9770a57629fb93a7d77029c3ac9591b19aa12b5442a7b1b7
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