Initial upload of logistic regression sentiment model

README.md

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+---
+license: mit
+tags:
+- sentiment-analysis
+- logistic-regression
+- sklearn
+- french
+language:
+- fr
+---
+
+# Carlito-25/sentiment-model-logistic
+
+Modèle de régression logistique pour l'analyse de sentiment
+
+## Usage
+
+```python
+from load_model import load_logistic_model, predict_sentiment
+import numpy as np
+
+# Charger le modèle
+model = load_logistic_model()
+
+# Prédiction (remplace par tes vraies features)
+features = np.array([...])  # Tes features TF-IDF ou Word2Vec
+result = predict_sentiment(model, features)
+print(result)
+```
+
+## Model Details
+
+- **Algorithm**: Logistic Regression (scikit-learn)
+- **Features**: TF-IDF/Word2Vec vectors
+- **Task**: Sentiment Analysis
+- **Training Data**: Custom French YouTube comments dataset

load_model.py

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+"""
+Script de chargement pour le modèle logistic regression
+"""
+import pickle
+import numpy as np
+from huggingface_hub import hf_hub_download
+
+def load_logistic_model(repo_id="Carlito-25/sentiment-model-logistic"):
+    """Charge le modèle logistic regression depuis Hugging Face"""
+    model_path = hf_hub_download(
+        repo_id=repo_id,
+        filename="model.pkl"
+    )
+    
+    with open(model_path, 'rb') as f:
+        model = pickle.load(f)
+    
+    return model
+
+def predict_sentiment(model, text_features):
+    """Prédiction avec le modèle logistic regression"""
+    if isinstance(text_features, list):
+        text_features = np.array(text_features).reshape(1, -1)
+    
+    prediction = model.predict(text_features)
+    probabilities = model.predict_proba(text_features)
+    
+    return {
+        'prediction': prediction[0],
+        'probabilities': probabilities[0].tolist()
+    }
+
+# Exemple d'usage
+if __name__ == "__main__":
+    model = load_logistic_model()
+    # Remplace par tes features réelles
+    dummy_features = np.random.rand(1, 100)  # Adapte selon tes features
+    result = predict_sentiment(model, dummy_features)
+    print(result)

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8707543052dcf62a09be5b23f7d3f8e9934bd4b3f965bb1d9587d47f76fb9e22
+size 63195069