Instructions to use hf-tiny-model-private/tiny-random-RoFormerForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-RoFormerForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-tiny-model-private/tiny-random-RoFormerForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RoFormerForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-RoFormerForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aeb207dfab641ff25a9c39754fbdbff11b89875f86de2b1e1b3cf95bfc161122
- Size of remote file:
- 13.3 MB
- SHA256:
- 87fc485e54adea989279a6d74f972c047fd92ccd4dee4d5e7ec11a58eec9acb9
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