Instructions to use hf-internal-testing/tiny-random-GPTNeoModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTNeoModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-GPTNeoModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTNeoModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-GPTNeoModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3231b062de42724a6575d442e341236226e6571bdf759af63bd9ed49013ccf0c
- Size of remote file:
- 1.45 MB
- SHA256:
- ff9bf78242191d96fa8e041e4083c45773aa6cf2093c21c949e1654e1cb87c0e
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