Fill-Mask
Transformers
Safetensors
bert
babylm
babylm-2026
strict-small
masked-language-modeling
accuracy-morph
Instructions to use alonsopg/babylm-2026-accuracy-morph-strict-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alonsopg/babylm-2026-accuracy-morph-strict-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="alonsopg/babylm-2026-accuracy-morph-strict-small")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("alonsopg/babylm-2026-accuracy-morph-strict-small") model = AutoModelForMaskedLM.from_pretrained("alonsopg/babylm-2026-accuracy-morph-strict-small") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "cls_token": "[CLS]", | |
| "do_lower_case": true, | |
| "is_local": false, | |
| "local_files_only": false, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 512, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "BertTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |