Instructions to use l3cube-pune/me-bert-mixed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/me-bert-mixed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="l3cube-pune/me-bert-mixed")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/me-bert-mixed") model = AutoModelForMaskedLM.from_pretrained("l3cube-pune/me-bert-mixed") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df1a441b4d35a30aaa3aa1dda9db977cd946ef83de27398f22b36bf3dda5807d
- Size of remote file:
- 712 MB
- SHA256:
- dfd9d4d4f391df2fdd9fee2a4070d048d85e066a937a821727a17dc8ab025684
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