Fill-Mask
Transformers
Safetensors
Korean
modernbert
neural-sparse
splade
opensearch
korean
information-retrieval
e-commerce
Instructions to use sewoong/korean-neural-sparse-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sewoong/korean-neural-sparse-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sewoong/korean-neural-sparse-encoder")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sewoong/korean-neural-sparse-encoder") model = AutoModelForMaskedLM.from_pretrained("sewoong/korean-neural-sparse-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8583b695bd737747352082b73fd27a131c747831285639ec771d43451bc1a91
- Size of remote file:
- 1.09 MB
- SHA256:
- ef9bebca9c6529bdefa19909059e07dfdfd7c2f8afeefbf4d230a784a3847d64
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