Fill-Mask
Transformers
PyTorch
Safetensors
gpt_bert
feature-extraction
gpt-bert
babylm
remote-code
custom_code
Instructions to use jumelet/gptbert-eus-250steps-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jumelet/gptbert-eus-250steps-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jumelet/gptbert-eus-250steps-base", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jumelet/gptbert-eus-250steps-base", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e65c4d3de55ddec75fe544244cd9af5027aa9745848bcb4bfa669977c472d953
- Size of remote file:
- 503 MB
- SHA256:
- 92b34d9df081a3908b844cd3119f56aa3c6a9fdbbc52187fbb785f99800007b2
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