Instructions to use hf-tiny-model-private/tiny-random-RobertaPreLayerNormForMaskedLM 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-RobertaPreLayerNormForMaskedLM 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-RobertaPreLayerNormForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RobertaPreLayerNormForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-RobertaPreLayerNormForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01c6b53e8b71a724087ffab25e75827678a2a137e30a7251aa8019130481b974
- Size of remote file:
- 379 kB
- SHA256:
- 27dc3249b79cdec3e97fc5d91c25b153a47f7aac43c38b3590c5992f727e49d7
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