Instructions to use ydshieh/tiny-random-BertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-BertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ydshieh/tiny-random-BertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-BertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("ydshieh/tiny-random-BertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 130548107c089426ec4dd98d835b096b48357b0bd28b49d6a290dba2ca4a539a
- Size of remote file:
- 389 kB
- SHA256:
- 0a82353efb77dbe1fd77fa9bee78260db25d8ca6b14ee42ef672394dee7ca428
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