Support non-streaming zipformer CTC ASR models (#2340)

This PR adds support for non-streaming Zipformer CTC ASR models across 
multiple language bindings, WebAssembly, examples, and CI workflows.

- Introduces a new OfflineZipformerCtcModelConfig in C/C++, Python, Swift, Java, Kotlin, Go, Dart, Pascal, and C# APIs
- Updates initialization, freeing, and recognition logic to include Zipformer CTC in WASM and Node.js
- Adds example scripts and CI steps for downloading, building, and running Zipformer CTC models

Model doc is available at
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-ctc/icefall/zipformer.html

java-api-examples/NonStreamingDecodeFileZipformerCtc.java

@@ -0,0 +1,50 @@
+// Copyright 2025 Xiaomi Corporation
+
+// This file shows how to use an offline Zipformer CTC model,
+// i.e., non-streaming Zipformer CTC model,
+// to decode files.
+import com.k2fsa.sherpa.onnx.*;
+
+public class NonStreamingDecodeFileZipformerCtc {
+  public static void main(String[] args) {
+    // please refer to
+    // https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-zipformer-ctc-zh-int8-2025-07-03.tar.bz2
+    // to download model files
+    String model = "./sherpa-onnx-zipformer-ctc-zh-int8-2025-07-03/model.int8.onnx";
+    String tokens = "./sherpa-onnx-zipformer-ctc-zh-int8-2025-07-03/tokens.txt";
+
+    String waveFilename = "./sherpa-onnx-zipformer-ctc-zh-int8-2025-07-03/test_wavs/0.wav";
+
+    WaveReader reader = new WaveReader(waveFilename);
+
+    OfflineZipformerCtcModelConfig zipformerCtc =
+        OfflineZipformerCtcModelConfig.builder().setModel(model).build();
+
+    OfflineModelConfig modelConfig =
+        OfflineModelConfig.builder()
+            .setZipformerCtc(zipformerCtc)
+            .setTokens(tokens)
+            .setNumThreads(1)
+            .setDebug(true)
+            .build();
+
+    OfflineRecognizerConfig config =
+        OfflineRecognizerConfig.builder()
+            .setOfflineModelConfig(modelConfig)
+            .setDecodingMethod("greedy_search")
+            .build();
+
+    OfflineRecognizer recognizer = new OfflineRecognizer(config);
+    OfflineStream stream = recognizer.createStream();
+    stream.acceptWaveform(reader.getSamples(), reader.getSampleRate());
+
+    recognizer.decode(stream);
+
+    String text = recognizer.getResult(stream).getText();
+
+    System.out.printf("filename:%s\nresult:%s\n", waveFilename, text);
+
+    stream.release();
+    recognizer.release();
+  }
+}