Text Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
Text Classification
Pytorch
Sentiment_Analysis
Deberta
text-embeddings-inference
Instructions to use RashidNLP/Amazon-Deberta-Base-Sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RashidNLP/Amazon-Deberta-Base-Sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RashidNLP/Amazon-Deberta-Base-Sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RashidNLP/Amazon-Deberta-Base-Sentiment") model = AutoModelForSequenceClassification.from_pretrained("RashidNLP/Amazon-Deberta-Base-Sentiment") - Notebooks
- Google Colab
- Kaggle
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This is a Deberta model finetuned on over 1 million reviews from Amazon's multi-reviews dataset.
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## Labels
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0 -> Negative
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1 -> Neutral
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2 -> Positive
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## How to use the model
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This is a Deberta model finetuned on over 1 million reviews from Amazon's multi-reviews dataset.
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## How to use the model
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