Instructions to use redonelach/bert-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use redonelach/bert-mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="redonelach/bert-mlm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("redonelach/bert-mlm") model = AutoModelForMaskedLM.from_pretrained("redonelach/bert-mlm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44bd0b5ae5562550a2137859cace49b8946b8b6588e8cd9a83c894446c4a055c
- Size of remote file:
- 2.24 GB
- SHA256:
- 7b586c56d849071c917571f909f648fb433a3e0a2b3028cfaf44169b12cf8216
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