Instructions to use hf-internal-testing/tiny-random-BertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-BertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-BertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b34cadef7415e1d107666637bb3167f954868975a1067a8576961c01bfb8a255
- Size of remote file:
- 706 kB
- SHA256:
- 50030d72fe2b87eebf763777b136897eefc4cd5d352f8b70c0e98d4a139a4be2
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