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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 80725f38c4e899f2bef2c71706e669d08042c9542f75255131cece7e650b2dbe
- Size of remote file:
- 1.65 MB
- SHA256:
- ce667bd8e86eb45fc98b26ea16b00d239cb6bc69c41a28bbdbe5e08dd26d9c86
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