Instructions to use hf-tiny-model-private/tiny-random-LukeModel 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-LukeModel 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-LukeModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-LukeModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-LukeModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f92ff320a4f692cf794e05142522018e16c69a3f0da7ffe427b3e6810c9ff62c
- Size of remote file:
- 6.81 MB
- SHA256:
- 31390d062f70af15af367c2a391815b3a0a9ae46bd3047a0d1002918d2a671b7
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