Instructions to use baebee/tagalog-autoc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use baebee/tagalog-autoc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="baebee/tagalog-autoc")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("baebee/tagalog-autoc") model = AutoModelForMaskedLM.from_pretrained("baebee/tagalog-autoc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f310071c1b2e8b571b6aa643c9c89ed9114d15e5087529f70f4b17419a0cc79
- Size of remote file:
- 1.78 GB
- SHA256:
- 602e2ee8aeb4446fc02823518aa77edb6509a76495998f2bd6943999ef0ad5a8
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