Instructions to use hf-internal-testing/tiny-random-RoFormerForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RoFormerForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-RoFormerForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RoFormerForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-RoFormerForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a0270f034115dceebb443a66cc28c69ac73600ed1e6a924a705056e9a009a38
- Size of remote file:
- 6.79 MB
- SHA256:
- cbac980711282a0ab01dc59e84ba3a2677b4f197bc662e87ece0711b92260c44
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