Instructions to use lysandre/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lysandre/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="lysandre/dummy-model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("lysandre/dummy-model") model = AutoModel.from_pretrained("lysandre/dummy-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 289447ff80e671392940f2bbaf7bd943f775c110c3a47c47498e5c8d086176c5
- Size of remote file:
- 433 MB
- SHA256:
- f7de2b430e6f88a2cc6eb64cdccc68f1804de957777b220bc83c6e2aa0e19a7f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.