Instructions to use hf-internal-testing/tiny-random-RobertaPreLayerNormForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RobertaPreLayerNormForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-RobertaPreLayerNormForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RobertaPreLayerNormForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-RobertaPreLayerNormForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67e00c65b59d25cbf16b39f6044bd1ff33b6702d55089b6add1bb1ecfe03c9d2
- Size of remote file:
- 359 kB
- SHA256:
- 23fde0be425af5b79588b894bf3ef9938f9bd7654d9e5bb9d5cca297199c0ac5
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