Instructions to use wiorz/gpt2_small_summarized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wiorz/gpt2_small_summarized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wiorz/gpt2_small_summarized")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wiorz/gpt2_small_summarized") model = AutoModelForSequenceClassification.from_pretrained("wiorz/gpt2_small_summarized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a09e250e2b2b4d378c1b3149d9cda9d628325024c6a3dcb8e5f5dbf4b7f11a46
- Size of remote file:
- 510 MB
- SHA256:
- 46dd30c462b3aa99c3d5ac3dbeca886d2ac010248423968d4ce301912f4ab50f
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