Update readme

README.md

@@ -81,7 +81,9 @@ pip install -e .
 
 ## Changelog
 
-- 🎉2026-02-13 Initial version of Twinkle✨ released, including SFT/PT/RL support for text models and serverless training capabilities on [ModelScope](https://modelscope.cn).
+- 🎉2026-02-13 Initial version of Twinkle✨ released, including SFT/PT/RL support for text models.
+We also made available serverless training capabilities on [ModelScope](https://modelscope.cn) via
+Tinker-compatible APIs.
 
 ## Training as a Service on ModelScope
 
@@ -105,8 +107,10 @@ We will be adding support for more models as new models are released. The follow
 supported on Twinkle✨ framework.
 
 >[!Note]
-> For serverless training service accessed via `base_url=https://www.modelscope.cn/twinkle`, it currently supports
-> one training base at a time, and currently it is [Qwen3-30B-A3B-Instruct-2507](https://modelscope.cn/models/Qwen/Qwen3-30B-A3B-Instruct-2507).
+> For serverless training service accessed via `base_url=https://www.modelscope.cn/twinkle`, it
+> is currently provided via the Tinker-compatible APIs. We will be rolling out services that support
+> both Tinker APIs, as well as the full-fledged Twinkle✨ native APIs. The serverless endpoint is backed
+> by one training base at a time, and currently it is [Qwen3-30B-A3B-Instruct-2507](https://modelscope.cn/models/Qwen/Qwen3-30B-A3B-Instruct-2507).
 
 
 | Model Type          | Model ID on [ModelScope](https://modelscope.cn)                                                                          | Requires             | Megatron Support | HF Model ID                                                                                                |
@@ -197,7 +201,7 @@ if __name__ == '__main__':
     train()
 ```
 
-### Using Tinker-Like API
+### Access the Serverless Training Services via Tinker-compatible API
 
 ```python
 import os

src/twinkle/metric/train_metric.py

@@ -44,7 +44,7 @@ def calculate(self):
                 self.lr = self.lr[0]
             if isinstance(self.lr, list):
                 for idx, lr in enumerate(self.lr):
-                    results[f'learning rate(param group {idx+1})'] = lr
+                    results[f'learning rate(param group {idx + 1})'] = lr
             else:
                 results['learning rate'] = self.lr
         if self.step is not None:
@@ -54,7 +54,7 @@ def calculate(self):
             if interval < 60:
                 results['total time elapse'] = f'{(time.time() - self.start_time):.0f} seconds'
             else:
-                results['total time elapse'] = f'{(time.time() - self.start_time)/60:.1f} minutes'
+                results['total time elapse'] = f'{(time.time() - self.start_time) / 60:.1f} minutes'
             results['speed'] = f'{speed:.2f} iters/s'
         self.reset()
         return results