Instructions to use math-similarity/Bert-MLM_arXiv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use math-similarity/Bert-MLM_arXiv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="math-similarity/Bert-MLM_arXiv")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("math-similarity/Bert-MLM_arXiv") model = AutoModelForMaskedLM.from_pretrained("math-similarity/Bert-MLM_arXiv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53fd363e6fc77c284a240b6ac02cebb2b7e5950bde07bf6ec796bf9dded5ef9c
- Size of remote file:
- 3.45 kB
- SHA256:
- 08cc3a17bd7cbdc6960f308043e823c292c7aa957c2a078363d9f5361e33a81b
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