Instructions to use dafqi/IndoBERTLarge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dafqi/IndoBERTLarge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dafqi/IndoBERTLarge")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dafqi/IndoBERTLarge") model = AutoModelForSequenceClassification.from_pretrained("dafqi/IndoBERTLarge", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dafqi/IndoBERTLarge: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/dafqi/IndoBERTLarge/resolve/main/training_args.bin
- Command line
-
hf download hf://dafqi/IndoBERTLarge/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dafqi/IndoBERTLarge/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 1e3a507dd08db29acb24e92b465ea5367a210246d8a08110fb2a902627bee2c6
- Size of remote file:
- 5.11 kB
- SHA256:
- 39b9a5b3f3669d8fc64f37abee5ab1b30d10f732e707c47f1c0d8e17701872ff
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