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:
- 9838f0d2046415576f6e04a8a9cb3e91ed6e28c3037b82e468e06806b8534bc6
- Size of remote file:
- 680 kB
- SHA256:
- b227a9010ec7bda240f13c969c3a65de046726c29f2cce239f609a945af29f62
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