Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use dafqi/IndoBERTL2-Rating-Prediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dafqi/IndoBERTL2-Rating-Prediction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dafqi/IndoBERTL2-Rating-Prediction")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dafqi/IndoBERTL2-Rating-Prediction") model = AutoModelForSequenceClassification.from_pretrained("dafqi/IndoBERTL2-Rating-Prediction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dafqi/IndoBERTL2-Rating-Prediction: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/dafqi/IndoBERTL2-Rating-Prediction/resolve/main/training_args.bin
- Command line
-
hf download hf://dafqi/IndoBERTL2-Rating-Prediction/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dafqi/IndoBERTL2-Rating-Prediction/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 48dc0dbecd3e4ce847cb9ecb9316e4bce0620fd55e77239c03f190b78a7dacad
- Size of remote file:
- 4.92 kB
- SHA256:
- 675d695fc45eb92d814f950ab8cf248c99bf21009a9a869f5dc05967c5ae8c7c
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