Text Classification
Transformers
Safetensors
Korean
bert
klue
korean
minwon
complaint
public-administration
text-embeddings-inference
Instructions to use atti433/minde-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use atti433/minde-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="atti433/minde-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("atti433/minde-classifier") model = AutoModelForSequenceClassification.from_pretrained("atti433/minde-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9fe17ed51717858f685b207ee8a0c81e16a317e91a8ebdd116494eb6df18d52
- Size of remote file:
- 4.83 kB
- SHA256:
- b2e387dd0f005f266c5dfe046fbe16fe2495ab09efcd66d4085762e6b7def63a
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