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:
- 4a5ed40aa23d9988695e8a20124361ffae81b32fccf807b963470d753af43247
- Size of remote file:
- 357 kB
- SHA256:
- 309af6412b277caa8955d6bba5a3fc74d50141b1987e14dbf2bc8b72d8c73f48
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