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:
- 3353ef2028cb88cdab85c69b858ae4918cbccfd351d0aa25b56db9c458f3653f
- Size of remote file:
- 680 kB
- SHA256:
- 624594dd230ccdaec550083dba87e19222ef16ea07b7e2a2af7bdbb55770680a
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