docs: add tested native Transformers pipeline entry point

examples/transformers/README.md

@@ -35,6 +35,53 @@ contains `text` and `reached_eos: true`. No access token is required for this
 public checkpoint. The model itself also runs through the short, no-clone
 [Python recipe](https://www.funasr.com/en/docs/native-transformers.html).
 
+## Use the Transformers pipeline API
+
+After the CPU installation above, this Python example also works without a
+repository clone. Explicitly select **`any-to-any`**: it uses the native processor
+and the checkpoint's structured transcription chat template.
+
+<!-- native-example: pipeline -->
+```python
+from copy import deepcopy
+import torch
+from transformers import pipeline
+
+torch.set_num_threads(4)
+transcriber = pipeline(
+    "any-to-any",
+    model="FunAudioLLM/Fun-ASR-Nano-2512-hf",
+    revision="d93b302ee7fd505e1b3576120fc142fc6f7820e1",
+    device="cpu", dtype=torch.float32, trust_remote_code=False, token=False,
+)
+messages = [{"role": "user", "content": [
+    {"type": "audio", "url": "https://huggingface.co/FunAudioLLM/Fun-ASR-Nano-2512/resolve/272c57b82523ada6fd87095e955f8e29100979ab/example/en.mp3"},
+    {"type": "language", "language": "英文"},
+]}]
+generation_config = deepcopy(transcriber.model.generation_config)
+generation_config.update(max_new_tokens=128, do_sample=False, num_beams=1)
+result = transcriber(
+    text=messages, return_full_text=False,
+    generate_kwargs={"generation_config": generation_config},
+    processor_kwargs={"audio_kwargs": {"sampling_rate": 16000}},
+)
+print(result[0]["generated_text"])
+```
+
+For a local recording, replace the audio entry with
+`{"type": "audio", "path": "recording.wav"}`. In this checkpoint's chat template,
+the language field uses `中文`, `英文` or `日文`; the higher-level
+`apply_transcription_request` helper additionally accepts ISO codes.
+`return_full_text=False` excludes the input conversation from the generated text.
+
+On Transformers 5.17.0, `pipeline("automatic-speech-recognition", ...)` is a
+different processing path: our pinned-checkpoint test fails with a floating-point
+token-index error. Do not replace `any-to-any` with that task or rely on automatic
+task inference. The example above was checked on the public English sample with
+CPU float32; it is not a pipeline GPU/batching, accuracy or capacity evaluation.
+The 128-token limit is for this short sample, not a completeness guarantee. Use
+the CLI below for explicit audio limits and EOS diagnostics.
+
 ## Your recordings and batches
 
 ```bash

tests/test_transformers_quickstart.py

@@ -16,6 +16,24 @@
 
 
 class NativeExampleTests(unittest.TestCase):
+    def test_pipeline_recipe_uses_registered_task_and_pinned_public_input(self):
+        guide = (ROOT / 'examples/transformers/README.md').read_text()
+        blocks = re.findall(r'<!-- native-example: pipeline -->\s*```python\n(.*?)```', guide, re.S)
+        self.assertEqual(len(blocks), 1, 'Missing unique runnable pipeline recipe')
+        tree = ast.parse(blocks[0])
+        calls = [n for n in ast.walk(tree) if isinstance(n, ast.Call)]
+        factory = next(n for n in calls if isinstance(n.func, ast.Name) and n.func.id == 'pipeline')
+        self.assertEqual(ast.literal_eval(factory.args[0]), 'any-to-any')
+        options = {kw.arg: kw.value for kw in factory.keywords}
+        self.assertEqual(ast.literal_eval(options['model']), native.MODEL_ID)
+        self.assertEqual(ast.literal_eval(options['revision']), native.REVISION)
+        self.assertEqual(ast.literal_eval(options['device']), 'cpu')
+        self.assertIs(ast.literal_eval(options['trust_remote_code']), False)
+        self.assertIs(ast.literal_eval(options['token']), False)
+        constants = {n.value for n in ast.walk(tree) if isinstance(n, ast.Constant) and isinstance(n.value, str)}
+        self.assertIn(f'https://huggingface.co/{native.SAMPLE_MODEL}/resolve/{native.SAMPLE_REVISION}/example/en.mp3', constants)
+        self.assertIn('automatic-speech-recognition', guide)
+
     def test_runtime_choices_fail_closed_without_silent_cpu_fallback(self):
         validate = getattr(native, 'validate_runtime', None)
         self.assertTrue(callable(validate), 'Explicit runtime validation is missing')