Fill-Mask
Transformers
Safetensors
English
theo_bert_base
masked-language-modeling
bible
theology
christianity
trust-remote-code
custom_code
Eval Results (legacy)
Instructions to use toranb/theo-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toranb/theo-bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="toranb/theo-bert-base", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("toranb/theo-bert-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3fc69ba6322c1b14991f0935b45683da95a941590d959fa18317665133cad4dc
- Size of remote file:
- 546 MB
- SHA256:
- fb9425642090f3523127bd8808f9a84c053c8c25f101775d0d759a460aad0c3a
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