Text Classification
Transformers
Safetensors
English
Korean
modernbert
fill-mask
Eval Results (legacy)
text-embeddings-inference
Instructions to use skt/A.X-Encoder-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use skt/A.X-Encoder-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="skt/A.X-Encoder-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("skt/A.X-Encoder-base") model = AutoModelForMaskedLM.from_pretrained("skt/A.X-Encoder-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 344b2137f7ae8053dbd88fd96d2870a97e6e06cbc389c0fd6c6f191ad8945ed6
- Size of remote file:
- 299 MB
- SHA256:
- c61b00328e5bb68bb18921baa0d4b0e83e76a57975e9cbdd9791850e25457089
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