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:
- 4737b43e96ba2e0e79401490eddfbd35538f16877b9ce8893750cb226db30871
- Size of remote file:
- 377 kB
- SHA256:
- 1758bf1c5d069e0bcd410cdeb4aa4d0617477f5f7f1fbbc372d1e362063ca98c
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