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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa634da017a68b7ccd3e5ab0181fe0f6c19ef030cfde328b5885299765d1c040
- Size of remote file:
- 738 MB
- SHA256:
- 9e3b0c1e8b418b930b1303b21c898e24267a844d92ac68f1f6b7de61eae2899a
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