Instructions to use DSI/human-directed-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DSI/human-directed-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DSI/human-directed-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DSI/human-directed-sentiment") model = AutoModelForSequenceClassification.from_pretrained("DSI/human-directed-sentiment") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("DSI/human-directed-sentiment")
model = AutoModelForSequenceClassification.from_pretrained("DSI/human-directed-sentiment")Quick Links
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Check out the documentation for more information.
** Human-Directed Sentiment Analysis in Arabic
A supervised training procedure to classify human-directed-sentiment in a text. We define the human-directed-sentiment as the polarity of one user towards a second person who is involved with him in a discussion.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DSI/human-directed-sentiment")