Instructions to use jcblaise/bert-tagalog-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jcblaise/bert-tagalog-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jcblaise/bert-tagalog-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jcblaise/bert-tagalog-base-uncased") model = AutoModelForMaskedLM.from_pretrained("jcblaise/bert-tagalog-base-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e81cf3ba583055f3fd1434b28c2878f12995c43db6cb68f446cb3462d7df12ea
- Size of remote file:
- 439 MB
- SHA256:
- a8083039480d985898aa20f0ebc664c56f457e4501166d483392b082dcc3f456
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