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:
- eeda2ca14ea54bef1eb8ee3f1d2840c45de984b51b0847e636b036b7c18ba531
- Size of remote file:
- 359 kB
- SHA256:
- 20e9a5317bd68f6653913bbdc5e0ee7e8e588920e163a9403cd2fccf6262f207
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