Fill-Mask
Transformers
Safetensors
English
deberta-v2
babylm
babylm-2026
strict-small
masked-language-modeling
whole-word-masking
simplification
sample-efficient-pretraining
Instructions to use go76dof/wwm_curriculum_simplification_40k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use go76dof/wwm_curriculum_simplification_40k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="go76dof/wwm_curriculum_simplification_40k")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("go76dof/wwm_curriculum_simplification_40k") model = AutoModelForMaskedLM.from_pretrained("go76dof/wwm_curriculum_simplification_40k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc5e8d357361518c7bfce2993d1e6d5622523b286516f0ea45532d09cdb3ddef
- Size of remote file:
- 919 kB
- SHA256:
- 1157bea377197596bde9a6f612a9fdcd0af3e51610ceb2b932b2120696dd3c64
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