Instructions to use dewifaj/text-classification-indobert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dewifaj/text-classification-indobert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dewifaj/text-classification-indobert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dewifaj/text-classification-indobert") model = AutoModelForSequenceClassification.from_pretrained("dewifaj/text-classification-indobert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dewifaj/text-classification-indobert: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/dewifaj/text-classification-indobert/resolve/main/training_args.bin
- Command line
-
hf download hf://dewifaj/text-classification-indobert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dewifaj/text-classification-indobert/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 7133d5a1b8230d0e958ccb513be48bd925772bd0f201873e33a25b1676ad83c9
- Size of remote file:
- 5.11 kB
- SHA256:
- f0a85d09a086dc6a62ae38c4fcbdbcf1d26aea55174fbf4ce9c3dbf68e8d4408
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