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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1debe8978794b36f662e2f30088e0e4cb17d80f709b8e70b104aaccc5694ba94
- Size of remote file:
- 445 kB
- SHA256:
- 4fb7f2e718883df86c863f4fb6f113078975d6a1254c648d1d96c9f910648244
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