Instructions to use wt3639/EduGBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wt3639/EduGBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="wt3639/EduGBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("wt3639/EduGBERT") model = AutoModelForMaskedLM.from_pretrained("wt3639/EduGBERT") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e87d9e74056bf7005fcb2d05b09e756c32d27245ba18d05d86619bf78ddbf49a
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size 1343123144
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