Instructions to use wesleymorris/summary-roberta-wording with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wesleymorris/summary-roberta-wording with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wesleymorris/summary-roberta-wording")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wesleymorris/summary-roberta-wording") model = AutoModelForSequenceClassification.from_pretrained("wesleymorris/summary-roberta-wording", device_map="auto") - 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 sha256:175b46c9d4b30f70944ba111ba27a423b9530cc2442b931594e9fbffc62e14e3
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size 498613948
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