Instructions to use ehdwns1516/klue-roberta-base_sae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ehdwns1516/klue-roberta-base_sae with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ehdwns1516/klue-roberta-base_sae")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ehdwns1516/klue-roberta-base_sae") model = AutoModelForSequenceClassification.from_pretrained("ehdwns1516/klue-roberta-base_sae") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
klue-roberta-base-sae
- This model trained with Korean dataset.
- Input sentence what you want to grasp intent.
- You can use English, but don't expect accuracy.
klue-roberta-base-kornli DEMO: Ainize DEMO
klue-roberta-base-kornli API: Ainize API
Overview
Language model: klue/roberta-base
Language: Korean
Training data: kor_sae
Eval data: kor_sae
Code: See Ainize Workspace
Usage
In Transformers
from transformers import AutoTokenizer, pipeline
tokenizer = AutoTokenizer.from_pretrained("ehdwns1516/klue-roberta-base-sae")
classifier = pipeline(
"text-classification",
model="ehdwns1516/klue-roberta-base-kornli",
return_all_scores=True,
)
context = "sentence what you want to grasp intent"
result = dict()
result[0] = classifier(context)[0]
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