fix: Fix argument order for training

examples/README.md

@@ -15,7 +15,7 @@ A simple binary sentiment classification example that covers:
 **Run the example:**
 ```bash
 cd examples
-uv run python basic_classification.py
+uv run --extra huggingface python basic_classification.py
 ```
 
 **What you'll learn:**
@@ -34,7 +34,7 @@ Demonstrates 3-class sentiment analysis (positive, negative, neutral):
 **Run the example:**
 ```bash
 cd examples
-uv run python multiclass_classification.py
+uv run  --extra huggingface python multiclass_classification.py
 ```
 
 **What you'll learn:**
@@ -53,7 +53,7 @@ Shows how to combine text and categorical features:
 **Run the example:**
 ```bash
 cd examples
-uv run python Using_additional_features.py
+uv run  --extra huggingface python Using_additional_features.py
 ```
 
 **What you'll learn:**
@@ -72,7 +72,7 @@ Explores advanced training configurations:
 **Run the example:**
 ```bash
 cd examples
-uv run python advanced_training.py
+uv run --extra huggingface python advanced_training.py
 ```
 
 **What you'll learn:**
@@ -93,10 +93,10 @@ Demonstrates model explainability with ASCII histogram visualizations:
 ```bash
 cd examples
 # Regular mode - analyze predefined examples
-uv run python simple_explainability_example.py
+uv run --extra huggingface python simple_explainability_example.py
 
 # Interactive mode - analyze your own text
-uv run python simple_explainability_example.py --interactive
+uv run --extra huggingface python simple_explainability_example.py --interactive
 ```
 
 **What you'll learn:**
@@ -111,19 +111,19 @@ uv run python simple_explainability_example.py --interactive
 To run any example:
 
 1. **Install dependencies:**
-   ```bash
-   uv sync
-   ```
+```bash
+uv sync
+```
 
 2. **Navigate to examples directory:**
-   ```bash
-   cd examples
-   ```
+```bash
+cd examples
+```
 
 3. **Run an example:**
-   ```bash
-   uv run python basic_classification.py
-   ```
+```bash
+uv --extra huggingface run python basic_classification.py
+```
 
 ## 📊 Example Outputs
 

examples/advanced_training.py

@@ -130,8 +130,9 @@ def main():
     )
 
     classifier.train(
-        X_train, y_train, X_val, y_val,
+        X_train, y_train, 
         training_config=training_config,
+        X_val=X_val, y_val=y_val,
         verbose=True
     )
 
@@ -172,13 +173,13 @@ def main():
         lr=1e-3,
         patience_early_stopping=7,
         num_workers=0,
-        cpu_run=False,  # Don't override accelerator from trainer_params
         trainer_params=advanced_trainer_params
     )
 
     advanced_classifier.train(
-        X_train, y_train, X_val, y_val,
+        X_train, y_train,
         training_config=advanced_training_config,
+        X_val=X_val, y_val=y_val,
         verbose=True
     )
 
@@ -206,14 +207,14 @@ def main():
         batch_size=16,  # Larger batch size for CPU
         lr=1e-3,
         patience_early_stopping=3,
-        cpu_run=False,  # Don't override accelerator from trainer_params
         num_workers=0,  # No multiprocessing for CPU
         trainer_params={'deterministic': True, 'accelerator': 'cpu'}
     )
 
     cpu_classifier.train(
-        X_train, y_train, X_val, y_val,
+        X_train, y_train,
         training_config=cpu_training_config,
+        X_val=X_val, y_val=y_val,
         verbose=True
     )
 
@@ -257,8 +258,9 @@ def main():
     )
 
     custom_classifier.train(
-        X_train, y_train, X_val, y_val,
+        X_train, y_train,
         training_config=custom_training_config,
+        X_val=X_val, y_val=y_val,
         verbose=True
     )
 

examples/basic_classification.py

@@ -130,8 +130,9 @@ def main():
         num_workers=0,  # Use 0 for simple examples to avoid multiprocessing issues
     )
     classifier.train(
-        X_train, y_train, X_val, y_val,
+        X_train, y_train, 
         training_config=training_config,
+        X_val=X_val, y_val=y_val,
         verbose=True
     )
     print("✅ Training completed!")

examples/multiclass_classification.py

@@ -128,8 +128,9 @@ def main():
         trainer_params={'deterministic': True}
     )
     classifier.train(
-        X_train, y_train, X_val, y_val,
+        X_train, y_train,
         training_config=training_config,
+        X_val=X_val, y_val=y_val,
         verbose=True
     )
     print("✅ Training completed!")

examples/simple_explainability_example.py

@@ -129,8 +129,9 @@ def main():
         trainer_params={'deterministic': True}
     )
     classifier.train(
-        X_train, y_train, X_val, y_val,
+        X_train, y_train, 
         training_config=training_config,
+        X_val=X_val, y_val=y_val,
         verbose=True
     )
     print("✅ Training completed!")

examples/using_additional_features.py

@@ -170,8 +170,9 @@ def train_and_evaluate_model(X, y, model_name, use_categorical=False, use_simple
     # Train model
     print("   🎯 Training model...")
     classifier.train(
-        X_train, y_train, X_val, y_val,
+        X_train, y_train,
         training_config=training_config,
+        X_val=X_val, y_val=y_val,
         verbose=True
     )
     training_time = time.time() - start_time