Text Classification
PEFT
Safetensors
English
roberta
sentiment-analysis
singlish
singapore
lora
qlora
Eval Results (legacy)
Instructions to use Yi-Siang/sg-sentiment-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Yi-Siang/sg-sentiment-roberta with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment-latest") model = PeftModel.from_pretrained(base_model, "Yi-Siang/sg-sentiment-roberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd3738e5f95e8fca0e5fc82deac99a3f833d05dea6f6a239f9cdd07ae2290e04
- Size of remote file:
- 2.41 MB
- SHA256:
- fed5121c71674f11902ec0ff0d0c3de94b274e47ca5be4d0a2f68aaaad7728f9
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