Instructions to use cmlformer/bertMLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cmlformer/bertMLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="cmlformer/bertMLM")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("cmlformer/bertMLM") model = AutoModel.from_pretrained("cmlformer/bertMLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a27f8017dfcc89f0c686c7eb6938117ef0c7b29c7d2bbc7a20c49086e16282c7
- Size of remote file:
- 128 MB
- SHA256:
- 0de46dc167df89eaa370e48dd5e9348d379edfc7b087d3dfee09a9bb742845fa
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