Instructions to use hf-internal-testing/tiny-random-ReformerForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ReformerForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-ReformerForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ReformerForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-ReformerForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4116eadeb18bf9b0c45c94aecc0a9f91d2b82a36bbf54e3da46ee72dfe246373
- Size of remote file:
- 432 kB
- SHA256:
- 4e0155e7ccfccc3bc6ddeb6101b0b07daf40d92333f2de9cc93ebfa84fed50da
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