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:
- aec24b93e870c3cbd0932e337e4497f095173dfc0366716b8e0148fe3d5e9d32
- Size of remote file:
- 6.79 MB
- SHA256:
- 037c866ced988dd3e82e16dc5b21f50c2dee08dfafa2e2367f5dbef774730fa1
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