Fill-Mask
Transformers
PyTorch
Safetensors
gpt_bert
feature-extraction
gpt-bert
babylm
remote-code
custom_code
Instructions to use jumelet/gptbert-kor-125steps-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jumelet/gptbert-kor-125steps-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jumelet/gptbert-kor-125steps-base", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jumelet/gptbert-kor-125steps-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60115ed976c1feb71916cd40a11bbc1ae014213972bc6b0a7515228a3c62f20c
- Size of remote file:
- 503 MB
- SHA256:
- b99e963e1f706e29fe5dc0a1b1cfb02ac8bee2d53c3898318f0892d865c0d565
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