Instructions to use unu-dev/krbert_ms2d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unu-dev/krbert_ms2d with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="unu-dev/krbert_ms2d")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("unu-dev/krbert_ms2d") model = AutoModelForSequenceClassification.from_pretrained("unu-dev/krbert_ms2d") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 326aa43a72236f2443fc8068a76da33702b8f599c97adde756818e819776cd4e
- Size of remote file:
- 395 MB
- SHA256:
- 5335782e57f2c3e35befe01a24af77d419e9b5047555ed2d6cb83f5ca917aeba
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