Fill-Mask
Transformers
PyTorch
Safetensors
gpt_bert
feature-extraction
gpt-bert
babylm
remote-code
custom_code
Instructions to use jumelet/gptbert-swe-100steps-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jumelet/gptbert-swe-100steps-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jumelet/gptbert-swe-100steps-small", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jumelet/gptbert-swe-100steps-small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b0aefef43b4bfefba040092eb416a50352541799a75889163854edc3beea39f
- Size of remote file:
- 145 MB
- SHA256:
- 6645e39e070783fbcd9042fdd540f1069bb6258031cc0225fdac5258e1fd0dc5
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