Instructions to use w11wo/javanese-roberta-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use w11wo/javanese-roberta-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="w11wo/javanese-roberta-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("w11wo/javanese-roberta-small") model = AutoModelForMaskedLM.from_pretrained("w11wo/javanese-roberta-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from w11wo/javanese-roberta-small: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/w11wo/javanese-roberta-small/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://w11wo/javanese-roberta-small/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/w11wo/javanese-roberta-small/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- f4a72cdcc825662dbef5b46948a4852d2539638af34fd9bd8daaad338d554263
- Size of remote file:
- 499 MB
- SHA256:
- 6f8a6e62ddb346f91deee18603fdb0333bacf49f3250e3ab43508bb255892b04
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