Instructions to use k4black/roberta-large-e-snli-classification-nli-default with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use k4black/roberta-large-e-snli-classification-nli-default with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="k4black/roberta-large-e-snli-classification-nli-default")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("k4black/roberta-large-e-snli-classification-nli-default") model = AutoModelForSequenceClassification.from_pretrained("k4black/roberta-large-e-snli-classification-nli-default") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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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:b6ca20bdb1311b590d7eddd6a024a0d7cc6d18f17200cfb8bde40d3ad5549a1c
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size 1421503716
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