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:
- f916c5a96897f6ee359038a4678905b5a845d0f9a39a86459534ecdf4ca539e8
- Size of remote file:
- 503 MB
- SHA256:
- 6d7cf5ea4099b182f574fe8b3553b4fc3f892d6bc7d08485041a00e8844a3ac9
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