Instructions to use ss531/koelectra with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ss531/koelectra with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ss531/koelectra")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ss531/koelectra") model = AutoModelForSequenceClassification.from_pretrained("ss531/koelectra") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2db8cf5ec16c678dc9df5a67ba06ecf93af819adbc93b1c716d90f0d6d8364db
- Size of remote file:
- 5.2 kB
- SHA256:
- 1fefb32bdf2d0379b3895a17d341988fbe5dcd2dbf63f463a6bd089f913da098
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