Instructions to use dejanseo/sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dejanseo/sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dejanseo/sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dejanseo/sentiment") model = AutoModelForSequenceClassification.from_pretrained("dejanseo/sentiment") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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albert/albert-base-v2
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## Labels
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sentiment_labels = {
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0: "very positive",
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1: "positive",
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5: "negative",
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6: "very negative"
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}
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# Sources of Training Data
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Synthetic. Llama3.
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albert/albert-base-v2
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## Labels
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```py
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sentiment_labels = {
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0: "very positive",
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1: "positive",
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5: "negative",
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6: "very negative"
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}
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```
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# Sources of Training Data
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Synthetic. Llama3.
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