Instructions to use hf-tiny-model-private/tiny-random-GPTNeoModel 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-GPTNeoModel 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-GPTNeoModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-GPTNeoModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-GPTNeoModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd24b8006ab1d699289c27ab2397cea278f4687579ccefa5a33d855b3e7c8940
- Size of remote file:
- 1.45 MB
- SHA256:
- bf00ad46c1839ddb5c7d02bb4ccd2eb942416059b9d948f6daf60689165067ab
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