Text Classification
Transformers
PyTorch
TensorFlow
English
deberta-v2
Sentiment-Analysis
Hate-Speech_Detection
NLP
Multi-task
Instructions to use Vivek-Sham/deberta-multitask-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vivek-Sham/deberta-multitask-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Vivek-Sham/deberta-multitask-sentiment-analysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Vivek-Sham/deberta-multitask-sentiment-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hate_speech_encoder.pkl from Vivek-Sham/deberta-multitask-sentiment-analysis: direct link, hf CLI and curl.
- Browser
- Download file 550 Bytes
-
https://huggingface.co/Vivek-Sham/deberta-multitask-sentiment-analysis/resolve/refs%2Fpr%2F1/hate_speech_encoder.pkl
- Command line
-
hf download hf://Vivek-Sham/deberta-multitask-sentiment-analysis@refs/pr/1/hate_speech_encoder.pkl
-
curl -L -o hate_speech_encoder.pkl https://huggingface.co/Vivek-Sham/deberta-multitask-sentiment-analysis/resolve/refs%2Fpr%2F1/hate_speech_encoder.pkl
550 Bytes
- Xet hash:
- 8899954fec23599d6a40a30a577837186ec23b07c5e5a3e03ac9528f63751e8b
- Size of remote file:
- 550 Bytes
- SHA256:
- e4afb1a05f6b49ff7ff8a5abab4e45cbf48e747c139b9e0ccc44fef397037274
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