Fill-Mask
Transformers
Safetensors
Korean
Literary Chinese
bert
text-generation
sillok
history
korean-history
classical-chinese
Instructions to use ddokbaro/SillokBert-Scratch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ddokbaro/SillokBert-Scratch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ddokbaro/SillokBert-Scratch")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ddokbaro/SillokBert-Scratch") model = AutoModelForMaskedLM.from_pretrained("ddokbaro/SillokBert-Scratch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ddokbaro/SillokBert-Scratch: direct link, hf CLI and curl.
- Browser
- Download file 47.9 MB
-
https://huggingface.co/ddokbaro/SillokBert-Scratch/resolve/main/tokenizer.json
- Command line
-
hf download hf://ddokbaro/SillokBert-Scratch/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ddokbaro/SillokBert-Scratch/resolve/main/tokenizer.json
47.9 MB
- Xet hash:
- 88a428c1d9c2d47c8c9797244b56c3f29c3d8104b7c896483fe422a36628c761
- Size of remote file:
- 47.9 MB
- SHA256:
- c9b6955f59143c79b51f35415728938395737613aa788ed435a146fe359c24e0
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