Instructions to use hf-tiny-model-private/tiny-random-RobertaForMaskedLM 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-RobertaForMaskedLM 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-RobertaForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RobertaForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-RobertaForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a5ec8680a6f6286f9ec209263c1f677888eb90efde07451369c145785a1f28a
- Size of remote file:
- 377 kB
- SHA256:
- 4dab4045c21293eaf8823ac864eeb9e76fd085c55b60939fadceb00085c4a091
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