Instructions to use hz53/roberta-base-boolq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hz53/roberta-base-boolq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hz53/roberta-base-boolq")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hz53/roberta-base-boolq") model = AutoModelForSequenceClassification.from_pretrained("hz53/roberta-base-boolq") - 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:cc2501c3c9f8b5376e5434a76de2df08f1b7462c74514bf098a00dceb6b849de
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size 498617024
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