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, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "TheoBertBaseForMaskedLM" | |
| ], | |
| "model_type": "theo_bert_base", | |
| "auto_map": { | |
| "AutoConfig": "configuration_theo_bert_base.TheoBertBaseConfig", | |
| "AutoModel": "modeling_theo_bert_base.TheoBertBaseModel", | |
| "AutoModelForMaskedLM": "modeling_theo_bert_base.TheoBertBaseForMaskedLM" | |
| }, | |
| "tokenizer_name": "google-bert/bert-base-uncased", | |
| "torch_dtype": "float32", | |
| "vocab_size": 30522, | |
| "n_layer": 12, | |
| "n_head": 8, | |
| "n_embd": 768, | |
| "seq_len": 256, | |
| "rope_base": 10000, | |
| "rope_cache_factor": 10, | |
| "hidden_size": 768, | |
| "num_hidden_layers": 12, | |
| "num_attention_heads": 8, | |
| "max_position_embeddings": 256, | |
| "pad_token_id": 0, | |
| "unk_token_id": 100, | |
| "cls_token_id": 101, | |
| "sep_token_id": 102, | |
| "mask_token_id": 103, | |
| "transformers_version": "5.2.0" | |
| } | |