Instructions to use hf-internal-testing/tiny-random-OpenAIGPTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-OpenAIGPTModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-OpenAIGPTModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-OpenAIGPTModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-OpenAIGPTModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2d449224245616ccd4fa49d2308b93730c71892f35bf641f8e739cb1017dfe7
- Size of remote file:
- 5.75 MB
- SHA256:
- 22aded5ec5635a7576e363383387d736178db65e0c6134689fb55b9f2bf1d39a
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