Update README.md

README.md

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   <img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm.svg" alt="Open in HuggingFace"/>
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-* **Fine-tuning guide on Colab:**
-
-<a target="_blank" href="https://colab.research.google.com/github/ylacombe/scripts_and_notebooks/blob/main/Finetuning_Parler_TTS_on_a_single_speaker_dataset.ipynb"> 
-  <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> 
-</a>
-
 **Parler-TTS Large v1** is a 2.2B-parameters text-to-speech (TTS) model, trained on 45K hours of audio data, that can generate high-quality, natural sounding speech with features that can be controlled using a simple text prompt (e.g. gender, background noise, speaking rate, pitch and reverberation).
 It is the second released model from the [Parler-TTS](https://github.com/huggingface/parler-tts) project, which aims to provide the community with TTS training resources and dataset pre-processing code.
 
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 * [🎲 Using a random voice](#🎲-random-voice)
 * [🎯 Using a specific speaker](#🎯-using-a-specific-speaker)
 * [Motivation](#motivation)
+* [Optimizing inference](https://github.com/huggingface/parler-tts/blob/main/INFERENCE.md)
 
 ## 🛠️ Usage
 
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 ```
 
 **Tips**:
+* We've set up an [inference guide](https://github.com/huggingface/parler-tts/blob/main/INFERENCE.md) to make generation faster. Think SDPA, torch.compile, batching and streaming!
 * Include the term "very clear audio" to generate the highest quality audio, and "very noisy audio" for high levels of background noise
 * Punctuation can be used to control the prosody of the generations, e.g. use commas to add small breaks in speech
 * The remaining speech features (gender, speaking rate, pitch and reverberation) can be controlled directly through the prompt