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Fayad11/
fine_tuned_emotion_inference_model

Name: fine_tuned_emotion_inference_model
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Emotion Inference Model (Fine-Tuned)

This is a fine-tuned text classification model for Emotion Detection. It predicts the underlying emotion of a given text sequence. The model is an asset evaluated alongside the broader NLP processing pipelines built by Fayad11.

Model Details

Model Identity: Fayad11/fine_tuned_emotion_inference_model
Architecture: Transformer-based sequence classification (e.g., BERT/DistilBERT fine-tuned)
Task: Multi-class text classification (Emotion Inference)
Language: English

Usage

You can use this model in your application via the Hugging Face transformers library, or locally alongside its associated EmotionPredictor wrapper (as demonstrated in the project notebooks).

Using `transformers` pipeline

python

from transformers import pipeline

# Load the model directly from the Hugging Face hub
emotion_classifier = pipeline("text-classification", model="Fayad11/fine_tuned_emotion_inference_model")

text = "I'm sad because I lost my keys."
result = emotion_classifier(text)

print(result)
# Output: [{'label': 'sadness', 'score': 0.98...}]

Fayad11/fine_tuned_emotion_inference_model

Emotion Inference Model (Fine-Tuned)

Model Details

Usage

Using transformers pipeline

Fayad11/
fine_tuned_emotion_inference_model

Using `transformers` pipeline