Fill-Mask
Transformers
PyTorch
Safetensors
gpt_bert
feature-extraction
gpt-bert
babylm
remote-code
custom_code
Instructions to use jumelet/gptbert-hrv-125steps-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jumelet/gptbert-hrv-125steps-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jumelet/gptbert-hrv-125steps-base", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jumelet/gptbert-hrv-125steps-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24f490174d7c8ce85472d8608495779b732029e6b78a109d2041601f340e2746
- Size of remote file:
- 503 MB
- SHA256:
- 87f8dae9775032c81fd6c61c2e06326826766fa4e39d36bb517babe1acbe437c
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