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
Update config.json
Browse files- config.json +3 -3
config.json
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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},
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"layer_norm_eps": 1e-07,
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"max_position_embeddings": 512,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"Negative": 0,
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"Neutral": 1,
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"Positive": 2
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},
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"layer_norm_eps": 1e-07,
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"max_position_embeddings": 512,
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