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
Download labels/emotion_labels.json from Praphull1/Sentimental-Analyzer-V3: direct link, hf CLI and curl.
- Browser
- Download file 554 Bytes
-
https://huggingface.co/Praphull1/Sentimental-Analyzer-V3/resolve/main/labels/emotion_labels.json
- Command line
-
hf download hf://Praphull1/Sentimental-Analyzer-V3/labels/emotion_labels.json
-
curl -L -o emotion_labels.json https://huggingface.co/Praphull1/Sentimental-Analyzer-V3/resolve/main/labels/emotion_labels.json
554 Bytes
Invalid JSON:Unexpected token '', "{
"0": "... is not valid JSON
| { | |
| "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" | |
| } | |