refactor: reorder model resolution in AutoModel to prioritize generic models in AutoModel

This ensures `AutoModel::fromPretrained`  returns the most generic model class when no specific task model is found, improving expected behavior and reducing accidental task-specific model selection.

Author: CodeWithKyrian

.github/workflows/release.yml

@@ -6,16 +6,20 @@
 
 use Codewithkyrian\Transformers\Models\Auto\AutoModel;
 use Codewithkyrian\Transformers\Processors\AutoProcessor;
+use Codewithkyrian\Transformers\Transformers;
 use Codewithkyrian\Transformers\Utils\Image;
+use Codewithkyrian\Transformers\Utils\ImageDriver;
 
 require_once './bootstrap.php';
 
 ini_set('memory_limit', '-1');
 
+Transformers::setup()->setImageDriver(ImageDriver::GD);
+
 $processor = AutoProcessor::fromPretrained('Xenova/yolov9-c_all');
 $model = AutoModel::fromPretrained('Xenova/yolov9-c_all');
 
-$image = Image::read(__DIR__.'/../images/multitask.png');
+$image = Image::read(__DIR__ . '/../images/multitask.png');
 
 $inputs = $processor($image);
 
@@ -42,10 +46,10 @@
 $fontScalingFactor = 0.75;
 $fontFile = '/Users/Kyrian/Library/Fonts/JosefinSans-Bold.ttf';
 $labelBoxHeight = $fontSize * 2 * $fontScalingFactor;
-$colors = array_map(fn () => sprintf('#%06x', mt_rand(0, 0xFFFFFF)), range(0, count($boxes) - 1));
+$colors = array_map(fn() => sprintf('#%06x', mt_rand(0, 0xFFFFFF)), range(0, count($boxes) - 1));
 
 foreach ($boxes as $box) {
-    $detectionLabel = $box['label'].'  '.round($box['score'], 2);
+    $detectionLabel = $box['label'] . '  ' . round($box['score'], 2);
     $color = $colors[array_search($box, $boxes)];
 
     $image = $image
@@ -69,4 +73,4 @@
         );
 }
 
-$image->save(__DIR__.'/../images/corgi-detected.jpg');
+$image->save(__DIR__ . '/../images/corgi-detected.jpg');

examples/misc/custom-object-detection.php

@@ -52,20 +52,20 @@ class AutoModel extends AutoModelBase
     ];
 
     const MODELS = [
-        ...self::ENCODER_ONLY_MODELS,
-        ...self::ENCODER_DECODER_MODELS,
-        ...self::DECODER_ONLY_MODELS,
-
-        ...AutoModelForSequenceClassification::MODELS,
-        ...AutoModelForTokenClassification::MODELS,
-        ...AutoModelForSeq2SeqLM::MODELS,
-        ...AutoModelForCausalLM::MODELS,
-        ...AutoModelForMaskedLM::MODELS,
-        ...AutoModelForQuestionAnswering::MODELS,
-        ...AutoModelForImageClassification::MODELS,
-        ...AutoModelForVision2Seq::MODELS,
-        ...AutoModelForObjectDetection::MODELS,
         ...AutoModelForZeroShotObjectDetection::MODELS,
+        ...AutoModelForObjectDetection::MODELS,
+        ...AutoModelForVision2Seq::MODELS,
+        ...AutoModelForImageClassification::MODELS,
+        ...AutoModelForQuestionAnswering::MODELS,
+        ...AutoModelForMaskedLM::MODELS,
+        ...AutoModelForCausalLM::MODELS,
+        ...AutoModelForSeq2SeqLM::MODELS,
+        ...AutoModelForTokenClassification::MODELS,
+        ...AutoModelForSequenceClassification::MODELS,
+
+        ...self::DECODER_ONLY_MODELS,
+        ...self::ENCODER_DECODER_MODELS,
+        ...self::ENCODER_ONLY_MODELS,
     ];
 
     const BASE_IF_FAIL = true;