Text Classification
Transformers
PyTorch
English
sentiment-analysis
emotion-classification
multi-label-classification
deberta-v3
nlp
Instructions to use Praphull1/Sentimental-Analyzer-V3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Praphull1/Sentimental-Analyzer-V3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Praphull1/Sentimental-Analyzer-V3")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Praphull1/Sentimental-Analyzer-V3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 554 Bytes
dfd384d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | {
"0": "admiration",
"1": "amusement",
"2": "anger",
"3": "annoyance",
"4": "approval",
"5": "caring",
"6": "confusion",
"7": "curiosity",
"8": "desire",
"9": "disappointment",
"10": "disapproval",
"11": "disgust",
"12": "embarrassment",
"13": "excitement",
"14": "fear",
"15": "gratitude",
"16": "grief",
"17": "joy",
"18": "love",
"19": "nervousness",
"20": "neutral",
"21": "optimism",
"22": "pride",
"23": "realization",
"24": "relief",
"25": "remorse",
"26": "sadness",
"27": "surprise"
}
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