Text Classification
Transformers
PyTorch
Safetensors
English
roberta
sentiment-analysis
huggingface
PyTorch
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("hasanmustafa0503/SentimentModel")
model = AutoModelForSequenceClassification.from_pretrained("hasanmustafa0503/SentimentModel")Quick Links
🧠 Sentiment Analysis Model
This model performs binary sentiment classification (Positive/Negative) on user-provided text inputs. It is trained to assist in mental health-related sentiment detection.
🚀 Usage
You can try this model via the Hugging Face Inference API or integrate it in your application using the transformers library.
🧪 Example
Input:
"I feel really hopeful today!"
Output:Positive
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hasanmustafa0503/SentimentModel")