Instructions to use Haitam03/bert-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Haitam03/bert-mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Haitam03/bert-mlm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Haitam03/bert-mlm") model = AutoModelForMaskedLM.from_pretrained("Haitam03/bert-mlm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90dbfb79506770d9c13c446ade56f62ccd63524276cb1df5e195b34c044bee0c
- Size of remote file:
- 5.2 kB
- SHA256:
- c902b6cb0f5066becb3da777b9b1dd2c53301de1d9e64a1e51a2b3b2710ca9ee
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