Instructions to use date3k2/gpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use date3k2/gpt2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="date3k2/gpt2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("date3k2/gpt2") model = AutoModelForSequenceClassification.from_pretrained("date3k2/gpt2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f175c64936c962b77e608272b05e5846c0aab648c0a15db3d68c8c4268b790c0
- Size of remote file:
- 498 MB
- SHA256:
- 0a8c741cd9643dde0d8e322ed1ec865f252df6078fac10015f3293a0aa208c0b
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