Instructions to use akahana/smallbert-javanese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akahana/smallbert-javanese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="akahana/smallbert-javanese")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("akahana/smallbert-javanese") model = AutoModelForMaskedLM.from_pretrained("akahana/smallbert-javanese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a31f91fcf5e842feeccaef2465be60274e8fa9654eb2baa9fd3ccd1a53ed1d7e
- Size of remote file:
- 5.18 kB
- SHA256:
- 3d3aa8062e0910ac698c6a4029eb9d1f2f4cfb60bf40aacbd3c44ca6cb0bc7be
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