Fill-Mask
Transformers
PyTorch
Safetensors
gpt_bert
feature-extraction
gpt-bert
babylm
remote-code
custom_code
Instructions to use jumelet/gptbert-hrv-100steps-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jumelet/gptbert-hrv-100steps-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jumelet/gptbert-hrv-100steps-small", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jumelet/gptbert-hrv-100steps-small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7eb3df7a022ba4a7ff6f86aa784d6633591b537c0321fc9a4999a82fd8070b42
- Size of remote file:
- 145 MB
- SHA256:
- 2424a057925977a231b05a59076fb9d431bfcd8aef84391b1a891ba04436200f
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