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:
- 54a0b31089b09007f43bbf33103b53af09257d1ffdfa299eac5d2190baa54347
- Size of remote file:
- 894 kB
- SHA256:
- 4cc3003bb4d2da8a8da6f9eb63e67660c008f560fad1433c7f9f4c062fc097d4
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