Text Classification
Transformers
PyTorch
Safetensors
English
roberta
sentiment-analysis
huggingface
PyTorch
Instructions to use hasanmustafa0503/SentimentModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hasanmustafa0503/SentimentModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hasanmustafa0503/SentimentModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hasanmustafa0503/SentimentModel") model = AutoModelForSequenceClassification.from_pretrained("hasanmustafa0503/SentimentModel") - Notebooks
- Google Colab
- Kaggle
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license: apache-2.0
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pipeline_tag: text-classification
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- sentiment-analysis
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# 🧠 Sentiment Analysis Model
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This model performs binary sentiment classification (Positive/Negative) on user-provided text inputs. It is trained to assist in mental health-related sentiment detection.
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language: en
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license: apache-2.0
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pipeline_tag: text-classification
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tags:
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- sentiment-analysis
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- roberta
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- text-classification
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- huggingface
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- transformers
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- PyTorch
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# 🧠 Sentiment Analysis Model
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This model performs binary sentiment classification (Positive/Negative) on user-provided text inputs. It is trained to assist in mental health-related sentiment detection.
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