Instructions to use hf-internal-testing/tiny-random-RobertaPreLayerNormForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RobertaPreLayerNormForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-RobertaPreLayerNormForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RobertaPreLayerNormForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-RobertaPreLayerNormForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 55e4ae076aea02dc3a1a7093f6e9a4b57d05cb8ca54cb3232cd5b5fd49c97464
- Size of remote file:
- 379 kB
- SHA256:
- 9b295bf99e3a225d8e2f0738e0a9c0aa1caabeaa5d72272b569b42645ff14166
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