Fill-Mask
Transformers
Safetensors
PyTorch
modernbert
entity-infilling
text-summarization
masked-modeling
Eval Results (legacy)
Instructions to use Glazkov/sum-entity-infilling-onehead with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Glazkov/sum-entity-infilling-onehead with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Glazkov/sum-entity-infilling-onehead")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Glazkov/sum-entity-infilling-onehead") model = AutoModelForMaskedLM.from_pretrained("Glazkov/sum-entity-infilling-onehead", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- efe89d2614a6957cb459491cb34fb5cba851a31850802e2a83893bbf7fe13323
- Size of remote file:
- 599 MB
- SHA256:
- 7f3d836162860151be36bae381b5554546fd84f9f970eb2eb71a1a033cb5d8e8
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