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

- Xet hash:
- b9c16dba21c21cefa6b761281218eed204367e6e5723aba8b37d3d4fa83a1a7b
- Size of remote file:
- 164 kB
- SHA256:
- 5e41e606567955055a7085c604d922728c926412eafe970faf1d1ec6a62f78b4
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