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:
- fbf18dca8739fbefd32517aacfd976d84f3aea535a80c6f41f05a23d5eff3f50
- Size of remote file:
- 438 MB
- SHA256:
- ac9136090478bbf8e65f2fd741a5371faea5902d5ad48ff897cbbaa026bd31da
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