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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from OpenLLM-Korea/A.X-Encoder-base: direct link, hf CLI and curl.
- Browser
- Download file 1.09 MB
-
https://huggingface.co/OpenLLM-Korea/A.X-Encoder-base/resolve/main/tokenizer.json
- Command line
-
hf download hf://OpenLLM-Korea/A.X-Encoder-base/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/OpenLLM-Korea/A.X-Encoder-base/resolve/main/tokenizer.json
1.09 MB
File too large to display, you can check the raw version instead.