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:
- fff34a6ac31360e6fb4b2e4183bfe0c904c9722d0aff3d341e5d3638e197678f
- Size of remote file:
- 416 kB
- SHA256:
- 8774412fc133c1456cd90d5d882d2b1b649ed110122ea41d1935076ff0e14b4b
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