Instructions to use ComCom/gpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ComCom/gpt2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ComCom/gpt2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ComCom/gpt2") model = AutoModel.from_pretrained("ComCom/gpt2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8bb89ca32161ac0dc358630edc9cadadcf01bae1a64d8b8055972b6e0330565e
- Size of remote file:
- 510 MB
- SHA256:
- c54796ba60499259315ba7cd46fdd66d2dbcc98edbafb144a9d75e09653d5cf9
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