Fill-Mask
Transformers
Safetensors
English
deberta-v2
babylm
deberta-v3
masked-lm
visual-grounding
data-efficient-pretraining
vision-init-sam
Instructions to use augustinian-babylm/deberta-base-100k-sam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use augustinian-babylm/deberta-base-100k-sam with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="augustinian-babylm/deberta-base-100k-sam")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("augustinian-babylm/deberta-base-100k-sam") model = AutoModelForMaskedLM.from_pretrained("augustinian-babylm/deberta-base-100k-sam", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 3,882 Bytes
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