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:
- f46bccd7fa0c7479bfdb613dc9c1bbfb8e0cfcbc2e5292025370f4dd7d949d83
- Size of remote file:
- 582 kB
- SHA256:
- 9a03eb6d8ca72195832b383f5a13ab6622daefe3b2d4c613f5958b381b4acc06
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