Instructions to use eunjin/koMHBERT-krbert-based-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eunjin/koMHBERT-krbert-based-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="eunjin/koMHBERT-krbert-based-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("eunjin/koMHBERT-krbert-based-v2") model = AutoModel.from_pretrained("eunjin/koMHBERT-krbert-based-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from eunjin/koMHBERT-krbert-based-v2: direct link, hf CLI and curl.
- Browser
- Download file 406 MB
-
https://huggingface.co/eunjin/koMHBERT-krbert-based-v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://eunjin/koMHBERT-krbert-based-v2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/eunjin/koMHBERT-krbert-based-v2/resolve/main/pytorch_model.bin
406 MB
- Xet hash:
- 1ccba78252b3bc1522a62e072f8933011f2205632d442bd89864a40bf70e4ded
- Size of remote file:
- 406 MB
- SHA256:
- bbab4eea4de20207059173e738939ac92c9aab5275a947ab98eea6c5e2796587
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