Instructions to use hf-internal-testing/tiny-random-RobertaForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RobertaForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-RobertaForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RobertaForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-RobertaForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d008d3f8a4e698bf319f4950a0485a0aa4b696e60423b8ef742f9e92263d23d
- Size of remote file:
- 465 kB
- SHA256:
- 9d59dc7b6e9869d20ec5d09f02e709bacf3cdb8d0faacc2c828be422b3a1d601
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