Instructions to use linhd-postdata/alberti-bert-base-multilingual-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use linhd-postdata/alberti-bert-base-multilingual-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="linhd-postdata/alberti-bert-base-multilingual-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("linhd-postdata/alberti-bert-base-multilingual-cased") model = AutoModelForMaskedLM.from_pretrained("linhd-postdata/alberti-bert-base-multilingual-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5ba9c1cf149b38f45a7bc030753cdaa9b2d20b08413b0a857168ce032eeda88
- Size of remote file:
- 712 MB
- SHA256:
- 74e76b0ba8bee646b78f7efdbdf3cd500ca183bc26439944fc1733f48a77f5ba
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