Fill-Mask
Transformers
PyTorch
Safetensors
gpt_bert
feature-extraction
gpt-bert
babylm
remote-code
custom_code
Instructions to use jumelet/gptbert-bug-100steps-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jumelet/gptbert-bug-100steps-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jumelet/gptbert-bug-100steps-small", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jumelet/gptbert-bug-100steps-small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download bug-2gpu-100steps.bin from jumelet/gptbert-bug-100steps-small: direct link, hf CLI and curl.
- Browser
- Download file 145 MB
-
https://huggingface.co/jumelet/gptbert-bug-100steps-small/resolve/main/bug-2gpu-100steps.bin
- Command line
-
hf download hf://jumelet/gptbert-bug-100steps-small/bug-2gpu-100steps.bin
-
curl -L -o bug-2gpu-100steps.bin https://huggingface.co/jumelet/gptbert-bug-100steps-small/resolve/main/bug-2gpu-100steps.bin
145 MB
- Xet hash:
- 56b491207ac93ad99a68009a725c979b6e25c2d3845b3bd69220af4734e77050
- Size of remote file:
- 145 MB
- SHA256:
- f5ced58f3065e228d6df8b24494b840b6a54d0e58062f66d06661c9cc1d40a0a
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