Update README.md

README.md

@@ -117,12 +117,7 @@ model_config = outetts.HFModelConfig_v2(
 interface = outetts.InterfaceHF(model_version="0.3", cfg=model_config)
 
 # You can create a speaker profile for voice cloning, which is compatible across all backends.
-# speaker = interface.create_speaker(
-#    audio_path="path/to/audio/file.wav",
-#    transcript=None,            # Set to None to use Whisper for transcription
-#    whisper_model="turbo",      # Optional: specify Whisper model (default: "turbo")
-#    whisper_device=None,        # Optional: specify device for Whisper (default: None)
-# )
+# speaker = interface.create_speaker(audio_path="path/to/audio/file.wav")
 # interface.save_speaker(speaker, "speaker.json")
 # speaker = interface.load_speaker("speaker.json")
 
@@ -144,8 +139,15 @@ output = interface.generate(config=gen_cfg)
 # Save the generated speech to a file
 output.save("output.wav")
 ```
+### Additional Usage Examples
+
+> [!IMPORTANT]
+> For additional usage examples and recommendations, visit the: [GitHub repository](https://github.com/edwko/OuteTTS?tab=readme-ov-file#usage).
+
+### Generation Performance
+
 > [!IMPORTANT]
-> ## For additional usage examples and recommendations, visit the [GitHub repository](https://github.com/edwko/OuteTTS?tab=readme-ov-file#usage).
+> The model performs best with 30-second generation batches. This window is reduced based on the length of your speaker samples. For example, if the speaker reference sample is 10 seconds, the effective window becomes approximately 20 seconds. I am currently working on adding batched generation capabilities to the library, along with further improvements that are not yet implemented.
 
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