Instructions to use ComCom/gpt2-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ComCom/gpt2-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ComCom/gpt2-large")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ComCom/gpt2-large") model = AutoModel.from_pretrained("ComCom/gpt2-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a22c1188edcd415519818dacc86d79825c09104cdb68bdb1f1b086bd0f0d1798
- Size of remote file:
- 3.13 GB
- SHA256:
- 6b5474d9a239e3025f710322e4ea01b690b4a75ccdb7de3d962ac586d2ad62ec
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