Instructions to use CYONG/slv-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CYONG/slv-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CYONG/slv-text-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CYONG/slv-text-classification") model = AutoModelForSequenceClassification.from_pretrained("CYONG/slv-text-classification") - 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 sha256:566bf9206d2cc9bd6009209d46a34738640d4b9a9fe48a05ce1fc559695b0f65
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size 55105088
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