Instructions to use mykor/conv-bert-base-ko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mykor/conv-bert-base-ko with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mykor/conv-bert-base-ko")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mykor/conv-bert-base-ko") model = AutoModelForMaskedLM.from_pretrained("mykor/conv-bert-base-ko", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mykor/conv-bert-base-ko: direct link, hf CLI and curl.
- Browser
- Download file 486 MB
-
https://huggingface.co/mykor/conv-bert-base-ko/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mykor/conv-bert-base-ko/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mykor/conv-bert-base-ko/resolve/main/pytorch_model.bin
486 MB
- Xet hash:
- 5fa488b6c6517c08d6463a207ddc2aeb8880801eb6a1e7de260ea945c1677402
- Size of remote file:
- 486 MB
- SHA256:
- 6ffc7e90dd3bc190116050f98f0ed3ef72b92b7c6ca8af25902804859a91d7e1
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