Instructions to use hf-tiny-model-private/tiny-random-MegatronBertForMaskedLM 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-MegatronBertForMaskedLM 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-MegatronBertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MegatronBertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-MegatronBertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b426e3240fefa523c02c510bd7a50b6a32d7ee1e740b4889cc58f495ba354fc
- Size of remote file:
- 913 kB
- SHA256:
- e42ab33c781b773d35fec3fbfc15b98bb1ebce0edca746bbab33a3a17b94b336
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