Instructions to use sileod/deberta-v3-base-tasksource-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sileod/deberta-v3-base-tasksource-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sileod/deberta-v3-base-tasksource-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sileod/deberta-v3-base-tasksource-sentiment") model = AutoModelForSequenceClassification.from_pretrained("sileod/deberta-v3-base-tasksource-sentiment") - 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 sha256:61a94123b9713686f36ffa2dc6ec89509ae68bf3bdc2d04cb74850ee4a324e36
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size 737722356
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