Instructions to use hf-tiny-model-private/tiny-random-GPT2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-GPT2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-GPT2Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-GPT2Model") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-GPT2Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 738355ac0193352135ff4cb8cf6a3913422f98aae773567eba26780762217c7b
- Size of remote file:
- 1.66 MB
- SHA256:
- 9deb4b1ee524b0c11162aaeeb4f5e574c7a550c193a738c3e6e0cc76d05e0a58
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