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/sentiment_labels.json from Praphull1/Sentimental-Analyzer-V3: direct link, hf CLI and curl.
- Browser
- Download file 111 Bytes
-
https://huggingface.co/Praphull1/Sentimental-Analyzer-V3/resolve/main/labels/sentiment_labels.json
- Command line
-
hf download hf://Praphull1/Sentimental-Analyzer-V3/labels/sentiment_labels.json
-
curl -L -o sentiment_labels.json https://huggingface.co/Praphull1/Sentimental-Analyzer-V3/resolve/main/labels/sentiment_labels.json
111 Bytes
Invalid JSON:Unexpected token '', "{
"0": "... is not valid JSON
| { | |
| "0": "Negative", | |
| "1": "Neutral", | |
| "2": "Positive", | |
| "3": "Very Negative", | |
| "4": "Very Positive" | |
| } | |