Instructions to use simonnedved/bert-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonnedved/bert-mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simonnedved/bert-mlm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simonnedved/bert-mlm") model = AutoModelForMaskedLM.from_pretrained("simonnedved/bert-mlm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f3e6a03fd3c558cfae931399d49d0e0f5a43a8aab970b5ff3c1ba9bd8fbe761
- Size of remote file:
- 437 MB
- SHA256:
- 2942ed21997833a972ddb1b59ef6e245cb84b11f174c713fe74010f3735b76d8
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