Instructions to use hf-tiny-model-private/tiny-random-OpenAIGPTModel 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-OpenAIGPTModel 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-OpenAIGPTModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-OpenAIGPTModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-OpenAIGPTModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b053831b0c1a8e1cd735f42c6482aac0d446412309fed007a5562f4a03c6cf4b
- Size of remote file:
- 5.77 MB
- SHA256:
- 426b2c80b5238769aef1a0c991e0b01eab8372dfde78bfdf8064008777025e30
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