Update README.md

README.md

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 ReConSE: Universal speech enhancement via recurrent control over a pretrained F5-TTS model.
 
+## Model Weights
+
+Two checkpoint files are provided:
+
+- **`model_70000_inference.pt`** — Full inference checkpoint. It contains the EMA weights for the complete ReConSE model: the F5-TTS v1 Base backbone, Recurrent ControlNet, and Qwen audio adapters. It excludes optimizer and scheduler states and the non-EMA training weights. The Qwen audio encoder and Vocos vocoder are not included.
+
+- **`model_70000_controlnet_adapter.pt`** — Compact EMA weights for the Recurrent ControlNet and Qwen audio adapters only. It does not contain the F5-TTS backbone, so it is **not a standalone checkpoint**.
+
+## Required External Assets
+
+Both checkpoint variants require the ReConSE code and configuration from the [GitHub repository](https://github.com/Lin-Johnson/ReConSE), including the model configuration and vocabulary file at `src/f5_tts/infer/examples/vocab.txt`.
+
+Because both checkpoints use Qwen audio adapters, download the [Qwen3-ASR-1.7B model](https://huggingface.co/Qwen/Qwen3-ASR-1.7B) for its audio encoder. The Qwen encoder weights are not bundled in either ReConSE checkpoint.
+
+The Vocos vocoder is also required to convert the generated mel spectrograms into audio. Download [Vocos mel-24kHz](https://huggingface.co/charactr/vocos-mel-24khz).
+
+### Using `model_70000_inference.pt`
+
+This checkpoint already contains the F5-TTS backbone weights. Load it with the ReConSE inference code and provide the external Qwen encoder and Vocos assets through the configuration.
+
+### Using `model_70000_controlnet_adapter.pt`
+
+This checkpoint requires the [F5-TTS v1 Base model weights](https://huggingface.co/SWivid/F5-TTS/tree/main/F5TTS_v1_Base), including `model_1250000.safetensors`.
+
+The current inference loader constructs the model architecture and then loads the supplied checkpoint. Since this file contains only ControlNet and adapter weights, using it directly would leave the F5-TTS backbone uninitialized. Modify the loading code to:
+
+1. Initialize the F5-TTS v1 Base backbone from its pretrained checkpoint.
+2. Load the ReConSE ControlNet and adapter weights on top of that backbone.
+
+The vocabulary used to construct the model must match the vocabulary expected by the checkpoint.
+
 ## Code
 
 [GitHub repository](https://github.com/Lin-Johnson/ReConSE)