Instructions to use nsadeq/InformBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nsadeq/InformBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nsadeq/InformBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nsadeq/InformBERT") model = AutoModelForMaskedLM.from_pretrained("nsadeq/InformBERT") - 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 sha256:9b108414ac38120a22465e61f66873b3b7445c58049972cd582f6a1d088dba71
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size 498821228
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