Instructions to use hf-internal-testing/tiny-random-GPT2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPT2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-GPT2Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPT2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-GPT2Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4604c6ad533a0a740855379f6cb77aa43f765c8dc5862edd48fec1375d165134
- Size of remote file:
- 1.66 MB
- SHA256:
- 725e6f17f6d47b1b90aa4e4ca9b95ff7d84b24228489bf40ca34dc98d5aebb61
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