Instructions to use hf-internal-testing/tiny-random-ReformerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ReformerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-ReformerModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ReformerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ReformerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 425e511cd75999b269c1ca5e30e2edc086f4135bd6113d07e6258e2d52f87234
- Size of remote file:
- 348 kB
- SHA256:
- ad2b54b562502b4294bf1afa4e7591765b52aec1cd8fd1f7e4b78c6b13007080
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