Instructions to use amc76/slangguard-pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use amc76/slangguard-pipeline with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("indobenchmark/indobert-base-p1") model = PeftModel.from_pretrained(base_model, "amc76/slangguard-pipeline") - Notebooks
- Google Colab
- Kaggle
SlangGuard champion adapter
The LoRA adapter that the SlangGuard retraining pipeline currently serves. Each commit in this repository is one champion, so the revision identifies the model. The pipeline replaces the files when a new model passes the promotion rule. For the released model with a full model card, see https://huggingface.co/amc76/slangguard-indobert-lora-replay and the project at https://github.com/Akmal76/slangguard.
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Base model
indobenchmark/indobert-base-p1