Fill-Mask
Transformers
PyTorch
Safetensors
gpt_bert
feature-extraction
gpt-bert
babylm
remote-code
custom_code
Instructions to use jumelet/gptbert-nor-100steps-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jumelet/gptbert-nor-100steps-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jumelet/gptbert-nor-100steps-base", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jumelet/gptbert-nor-100steps-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69c716c79ea5a8ab8c15a6d6dc157b75ef5e12128e9b833155549b5ed56fd245
- Size of remote file:
- 145 MB
- SHA256:
- ef56b6055b91d7f6d6c8ce08f2de4c7a37b461e768ff5b383972864064724c68
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