Instructions to use acul3/roberta-base-indo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use acul3/roberta-base-indo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="acul3/roberta-base-indo")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("acul3/roberta-base-indo") model = AutoModelForMaskedLM.from_pretrained("acul3/roberta-base-indo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2aff64de2c7a7699fb43a057f91085d94c62d6c0b86612ac535abb26809e261f
- Size of remote file:
- 499 MB
- SHA256:
- 3d91c6a8086e7e5de6efe9847965b95b54f170dc9828b3eb705d5da1be78541a
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