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:
- 0b5d0990d733c491326067c8aca5bd93ad07b497f40344e0339b570ce80ebea3
- Size of remote file:
- 1.47 MB
- SHA256:
- 8c1a4ebb3fedc0f48f98e7bb3d54e755d691b986a8bde830404684bcb2770ef3
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