diff --git a/.gitignore b/.gitignore
index 06859efb..38a7d504 100644
--- a/.gitignore
+++ b/.gitignore
@@ -42,3 +42,4 @@ candle-wasm-examples/**/config*.json
 .idea/*
 __pycache__
 out.safetensors
+out.wav
diff --git a/candle-examples/examples/parler-tts/decode.py b/candle-examples/examples/parler-tts/decode.py
index b79ebda1..8942d32e 100644
--- a/candle-examples/examples/parler-tts/decode.py
+++ b/candle-examples/examples/parler-tts/decode.py
@@ -5,6 +5,7 @@ from parler_tts import DACModel
 
 tensors = load_file("out.safetensors")
 dac_model = DACModel.from_pretrained("parler-tts/dac_44khZ_8kbps")
+print(dac_model.model)
 output_ids = tensors["codes"][None, None]
 print(output_ids, "\n", output_ids.shape)
 batch_size = 1
diff --git a/candle-examples/examples/parler-tts/main.rs b/candle-examples/examples/parler-tts/main.rs
index e6cf3c44..4e3730e2 100644
--- a/candle-examples/examples/parler-tts/main.rs
+++ b/candle-examples/examples/parler-tts/main.rs
@@ -7,7 +7,7 @@ extern crate accelerate_src;
 use anyhow::Error as E;
 use clap::Parser;
 
-use candle::{DType, Tensor};
+use candle::{DType, IndexOp, Tensor};
 use candle_nn::VarBuilder;
 use candle_transformers::models::parler_tts::{Config, Model};
 use tokenizers::Tokenizer;
@@ -36,7 +36,7 @@ struct Args {
     description: String,
 
     /// The temperature used to generate samples.
-    #[arg(long, default_value_t = 1.0)]
+    #[arg(long, default_value_t = 0.0)]
     temperature: f64,
 
     /// Nucleus sampling probability cutoff.
@@ -82,6 +82,10 @@ struct Args {
 
     #[arg(long, default_value_t = 512)]
     max_steps: usize,
+
+    /// The output wav file.
+    #[arg(long, default_value = "out.wav")]
+    out_file: String,
 }
 
 fn main() -> anyhow::Result<()> {
@@ -152,24 +156,32 @@ fn main() -> anyhow::Result<()> {
         .get_ids()
         .to_vec();
     let description_tokens = Tensor::new(description_tokens, &device)?.unsqueeze(0)?;
-    println!("{description_tokens}");
-
     let prompt_tokens = tokenizer
         .encode(args.prompt, true)
         .map_err(E::msg)?
         .get_ids()
         .to_vec();
     let prompt_tokens = Tensor::new(prompt_tokens, &device)?.unsqueeze(0)?;
-    println!("{prompt_tokens}");
-
     let lp = candle_transformers::generation::LogitsProcessor::new(
         args.seed,
         Some(args.temperature),
         args.top_p,
     );
+    println!("starting generation...");
     let codes = model.generate(&prompt_tokens, &description_tokens, lp, args.max_steps)?;
-    println!("{codes}");
+    println!("generated codes\n{codes}");
     let codes = codes.to_dtype(DType::I64)?;
     codes.save_safetensors("codes", "out.safetensors")?;
+    let codes = codes.unsqueeze(0)?;
+    let pcm = model
+        .audio_encoder
+        .decode_codes(&codes.to_device(&device)?)?;
+    println!("{pcm}");
+    let pcm = pcm.i((0, 0))?;
+    let pcm = candle_examples::audio::normalize_loudness(&pcm, 24_000, true)?;
+    let pcm = pcm.to_vec1::<f32>()?;
+    let mut output = std::fs::File::create(&args.out_file)?;
+    candle_examples::wav::write_pcm_as_wav(&mut output, &pcm, config.audio_encoder.sampling_rate)?;
+
     Ok(())
 }
diff --git a/candle-transformers/src/models/dac.rs b/candle-transformers/src/models/dac.rs
new file mode 100644
index 00000000..fa6c8c71
--- /dev/null
+++ b/candle-transformers/src/models/dac.rs
@@ -0,0 +1,376 @@
+/// Adapted from https://github.com/descriptinc/descript-audio-codec
+use crate::models::encodec;
+use candle::{IndexOp, Result, Tensor, D};
+use candle_nn::{Conv1d, Conv1dConfig, ConvTranspose1d, ConvTranspose1dConfig, VarBuilder};
+
+#[derive(serde::Deserialize, Debug, Clone)]
+pub struct Config {
+    pub num_codebooks: usize,
+    pub model_bitrate: u32,
+    pub codebook_size: usize,
+    pub latent_dim: usize,
+    pub frame_rate: u32,
+    pub sampling_rate: u32,
+}
+
+#[derive(Debug, Clone)]
+pub struct Snake1d {
+    alpha: Tensor,
+}
+
+impl Snake1d {
+    pub fn new(channels: usize, vb: VarBuilder) -> Result<Self> {
+        let alpha = vb.get((1, channels, 1), "alpha")?;
+        Ok(Self { alpha })
+    }
+}
+
+impl candle::Module for Snake1d {
+    fn forward(&self, xs: &Tensor) -> Result<Tensor> {
+        let xs_shape = xs.shape();
+        let xs = xs.flatten_from(2)?;
+        let sin = self.alpha.broadcast_mul(&xs)?.sin()?;
+        let sin = (&sin * &sin)?;
+        (xs + (&self.alpha + 1e-9)?.recip()?.broadcast_mul(&sin)?)?.reshape(xs_shape)
+    }
+}
+
+#[derive(Debug, Clone)]
+pub struct ResidualUnit {
+    snake1: Snake1d,
+    conv1: Conv1d,
+    snake2: Snake1d,
+    conv2: Conv1d,
+}
+
+impl ResidualUnit {
+    pub fn new(dim: usize, dilation: usize, vb: VarBuilder) -> Result<Self> {
+        let pad = ((7 - 1) * dilation) / 2;
+        let vb = vb.pp("block");
+        let snake1 = Snake1d::new(dim, vb.pp(0))?;
+        let cfg1 = Conv1dConfig {
+            dilation,
+            padding: pad,
+            ..Default::default()
+        };
+        let conv1 = encodec::conv1d_weight_norm(dim, dim, 7, cfg1, vb.pp(1))?;
+        let snake2 = Snake1d::new(dim, vb.pp(2))?;
+        let conv2 = encodec::conv1d_weight_norm(dim, dim, 1, Default::default(), vb.pp(3))?;
+        Ok(Self {
+            snake1,
+            conv1,
+            snake2,
+            conv2,
+        })
+    }
+}
+
+impl candle::Module for ResidualUnit {
+    fn forward(&self, xs: &Tensor) -> Result<Tensor> {
+        let ys = xs
+            .apply(&self.snake1)?
+            .apply(&self.conv1)?
+            .apply(&self.snake2)?
+            .apply(&self.conv2)?;
+        let pad = (xs.dim(D::Minus1)? - ys.dim(D::Minus1)?) / 2;
+        if pad > 0 {
+            &ys + xs.narrow(D::Minus1, pad, ys.dim(D::Minus1)?)
+        } else {
+            ys + xs
+        }
+    }
+}
+
+#[derive(Debug, Clone)]
+pub struct EncoderBlock {
+    res1: ResidualUnit,
+    res2: ResidualUnit,
+    res3: ResidualUnit,
+    snake1: Snake1d,
+    conv1: Conv1d,
+}
+
+impl EncoderBlock {
+    pub fn new(dim: usize, stride: usize, vb: VarBuilder) -> Result<Self> {
+        let vb = vb.pp("block");
+        let res1 = ResidualUnit::new(dim / 2, 1, vb.pp(0))?;
+        let res2 = ResidualUnit::new(dim / 2, 3, vb.pp(1))?;
+        let res3 = ResidualUnit::new(dim / 2, 9, vb.pp(2))?;
+        let snake1 = Snake1d::new(dim / 2, vb.pp(3))?;
+        let cfg1 = Conv1dConfig {
+            stride,
+            padding: (stride + 1) / 2,
+            ..Default::default()
+        };
+        let conv1 = encodec::conv1d_weight_norm(dim / 2, dim, 2 * stride, cfg1, vb.pp(4))?;
+        Ok(Self {
+            res1,
+            res2,
+            res3,
+            snake1,
+            conv1,
+        })
+    }
+}
+
+impl candle::Module for EncoderBlock {
+    fn forward(&self, xs: &Tensor) -> Result<Tensor> {
+        xs.apply(&self.res1)?
+            .apply(&self.res2)?
+            .apply(&self.res3)?
+            .apply(&self.snake1)?
+            .apply(&self.conv1)
+    }
+}
+
+#[derive(Debug, Clone)]
+pub struct Encoder {
+    conv1: Conv1d,
+    blocks: Vec<EncoderBlock>,
+    snake1: Snake1d,
+    conv2: Conv1d,
+}
+
+impl candle::Module for Encoder {
+    fn forward(&self, xs: &Tensor) -> Result<Tensor> {
+        let mut xs = xs.apply(&self.conv1)?;
+        for block in self.blocks.iter() {
+            xs = xs.apply(block)?
+        }
+        xs.apply(&self.snake1)?.apply(&self.conv2)
+    }
+}
+
+impl Encoder {
+    pub fn new(
+        mut d_model: usize,
+        strides: &[usize],
+        d_latent: usize,
+        vb: VarBuilder,
+    ) -> Result<Self> {
+        let vb = vb.pp("block");
+        let cfg1 = Conv1dConfig {
+            padding: 3,
+            ..Default::default()
+        };
+        let conv1 = encodec::conv1d_weight_norm(1, d_model, 7, cfg1, vb.pp(0))?;
+        let mut blocks = Vec::with_capacity(strides.len());
+        for (block_idx, stride) in strides.iter().enumerate() {
+            d_model *= 2;
+            let block = EncoderBlock::new(d_model, *stride, vb.pp(block_idx + 1))?;
+            blocks.push(block)
+        }
+        let snake1 = Snake1d::new(d_model, vb.pp(strides.len() + 1))?;
+        let cfg2 = Conv1dConfig {
+            padding: 1,
+            ..Default::default()
+        };
+        let conv2 =
+            encodec::conv1d_weight_norm(d_model, d_latent, 3, cfg2, vb.pp(strides.len() + 2))?;
+        Ok(Self {
+            conv1,
+            blocks,
+            snake1,
+            conv2,
+        })
+    }
+}
+
+#[derive(Debug, Clone)]
+pub struct DecoderBlock {
+    snake1: Snake1d,
+    conv_tr1: ConvTranspose1d,
+    res1: ResidualUnit,
+    res2: ResidualUnit,
+    res3: ResidualUnit,
+}
+
+impl DecoderBlock {
+    pub fn new(in_dim: usize, out_dim: usize, stride: usize, vb: VarBuilder) -> Result<Self> {
+        let vb = vb.pp("block");
+        let snake1 = Snake1d::new(in_dim, vb.pp(0))?;
+        let cfg = ConvTranspose1dConfig {
+            stride,
+            padding: (stride + 1) / 2,
+            ..Default::default()
+        };
+        let conv_tr1 = encodec::conv_transpose1d_weight_norm(
+            in_dim,
+            out_dim,
+            2 * stride,
+            true,
+            cfg,
+            vb.pp(1),
+        )?;
+        let res1 = ResidualUnit::new(out_dim, 1, vb.pp(2))?;
+        let res2 = ResidualUnit::new(out_dim, 3, vb.pp(3))?;
+        let res3 = ResidualUnit::new(out_dim, 9, vb.pp(4))?;
+        Ok(Self {
+            snake1,
+            conv_tr1,
+            res1,
+            res2,
+            res3,
+        })
+    }
+}
+
+impl candle_nn::Module for DecoderBlock {
+    fn forward(&self, xs: &Tensor) -> Result<Tensor> {
+        xs.apply(&self.snake1)?
+            .apply(&self.conv_tr1)?
+            .apply(&self.res1)?
+            .apply(&self.res2)?
+            .apply(&self.res3)
+    }
+}
+
+#[derive(Debug, Clone)]
+pub struct Decoder {
+    conv1: Conv1d,
+    blocks: Vec<DecoderBlock>,
+    snake1: Snake1d,
+    conv2: Conv1d,
+}
+
+impl Decoder {
+    pub fn new(
+        in_c: usize,
+        mut channels: usize,
+        rates: &[usize],
+        d_out: usize,
+        vb: VarBuilder,
+    ) -> Result<Self> {
+        let vb = vb.pp("model");
+        let cfg1 = Conv1dConfig {
+            padding: 3,
+            ..Default::default()
+        };
+        let conv1 = encodec::conv1d_weight_norm(in_c, channels, 7, cfg1, vb.pp(0))?;
+        let mut blocks = Vec::with_capacity(rates.len());
+        for (idx, stride) in rates.iter().enumerate() {
+            let block = DecoderBlock::new(channels, channels / 2, *stride, vb.pp(idx + 1))?;
+            channels /= 2;
+            blocks.push(block)
+        }
+        let snake1 = Snake1d::new(channels, vb.pp(rates.len() + 1))?;
+        let conv2 = encodec::conv1d_weight_norm(channels, d_out, 7, cfg1, vb.pp(rates.len() + 2))?;
+        Ok(Self {
+            conv1,
+            blocks,
+            snake1,
+            conv2,
+        })
+    }
+}
+
+impl candle::Module for Decoder {
+    fn forward(&self, xs: &Tensor) -> Result<Tensor> {
+        let mut xs = xs.apply(&self.conv1)?;
+        for block in self.blocks.iter() {
+            xs = xs.apply(block)?
+        }
+        xs.apply(&self.snake1)?.apply(&self.conv2)
+    }
+}
+
+#[allow(unused)]
+#[derive(Clone, Debug)]
+pub struct VectorQuantizer {
+    in_proj: Conv1d,
+    out_proj: Conv1d,
+    codebook: candle_nn::Embedding,
+}
+
+impl VectorQuantizer {
+    pub fn new(in_dim: usize, cb_size: usize, cb_dim: usize, vb: VarBuilder) -> Result<Self> {
+        let in_proj =
+            encodec::conv1d_weight_norm(in_dim, cb_dim, 1, Default::default(), vb.pp("in_proj"))?;
+        let out_proj =
+            encodec::conv1d_weight_norm(cb_dim, in_dim, 1, Default::default(), vb.pp("out_proj"))?;
+        let codebook = candle_nn::embedding(cb_size, cb_dim, vb.pp("codebook"))?;
+        Ok(Self {
+            in_proj,
+            out_proj,
+            codebook,
+        })
+    }
+
+    pub fn embed_code(&self, embed_id: &Tensor) -> Result<Tensor> {
+        embed_id.apply(&self.codebook)
+    }
+
+    pub fn decode_code(&self, embed_id: &Tensor) -> Result<Tensor> {
+        self.embed_code(embed_id)?.transpose(1, 2)
+    }
+}
+
+#[derive(Clone, Debug)]
+pub struct ResidualVectorQuantizer {
+    quantizers: Vec<VectorQuantizer>,
+}
+
+impl ResidualVectorQuantizer {
+    pub fn new(
+        input_dim: usize,
+        n_codebooks: usize,
+        cb_size: usize,
+        cb_dim: usize,
+        vb: VarBuilder,
+    ) -> Result<Self> {
+        let vb = &vb.pp("quantizers");
+        let quantizers = (0..n_codebooks)
+            .map(|i| VectorQuantizer::new(input_dim, cb_size, cb_dim, vb.pp(i)))
+            .collect::<Result<Vec<_>>>()?;
+        Ok(Self { quantizers })
+    }
+
+    pub fn from_codes(&self, codes: &Tensor) -> Result<Tensor> {
+        let mut sum = None;
+        for (idx, quantizer) in self.quantizers.iter().enumerate() {
+            let z_p_i = quantizer.decode_code(&codes.i((.., idx))?)?;
+            let z_q_i = z_p_i.apply(&quantizer.out_proj)?;
+            let s = match sum {
+                None => z_q_i,
+                Some(s) => (s + z_q_i)?,
+            };
+            sum = Some(s)
+        }
+        match sum {
+            Some(s) => Ok(s),
+            None => candle::bail!("empty codebooks"),
+        }
+    }
+}
+
+#[derive(Debug, Clone)]
+pub struct Model {
+    pub encoder: Encoder,
+    pub quantizer: ResidualVectorQuantizer,
+    pub decoder: Decoder,
+}
+
+impl Model {
+    pub fn new(cfg: &Config, vb: VarBuilder) -> Result<Self> {
+        let vb = vb.pp("model");
+        let encoder = Encoder::new(64, &[2, 4, 8, 8], cfg.latent_dim, vb.pp("encoder"))?;
+        let quantizer = ResidualVectorQuantizer::new(
+            cfg.latent_dim,
+            cfg.num_codebooks,
+            cfg.codebook_size,
+            8,
+            vb.pp("quantizer"),
+        )?;
+        let decoder = Decoder::new(cfg.latent_dim, 1536, &[8, 8, 4, 2], 1, vb.pp("decoder"))?;
+        Ok(Self {
+            encoder,
+            decoder,
+            quantizer,
+        })
+    }
+
+    pub fn decode_codes(&self, audio_codes: &Tensor) -> Result<Tensor> {
+        let audio_values = self.quantizer.from_codes(audio_codes)?;
+        audio_values.apply(&self.decoder)
+    }
+}
diff --git a/candle-transformers/src/models/encodec.rs b/candle-transformers/src/models/encodec.rs
index fb70fb52..ba6686f6 100644
--- a/candle-transformers/src/models/encodec.rs
+++ b/candle-transformers/src/models/encodec.rs
@@ -136,7 +136,7 @@ pub fn conv1d_weight_norm(
     Ok(Conv1d::new(weight, Some(bias), config))
 }
 
-fn conv_transpose1d_weight_norm(
+pub fn conv_transpose1d_weight_norm(
     in_c: usize,
     out_c: usize,
     kernel_size: usize,
diff --git a/candle-transformers/src/models/mod.rs b/candle-transformers/src/models/mod.rs
index 83d13a7b..cc83cf7b 100644
--- a/candle-transformers/src/models/mod.rs
+++ b/candle-transformers/src/models/mod.rs
@@ -9,6 +9,7 @@ pub mod clip;
 pub mod codegeex4_9b;
 pub mod convmixer;
 pub mod convnext;
+pub mod dac;
 pub mod depth_anything_v2;
 pub mod dinov2;
 pub mod dinov2reg4;
diff --git a/candle-transformers/src/models/parler_tts.rs b/candle-transformers/src/models/parler_tts.rs
index 9c66c93a..16023a7c 100644
--- a/candle-transformers/src/models/parler_tts.rs
+++ b/candle-transformers/src/models/parler_tts.rs
@@ -31,6 +31,7 @@ pub struct Config {
     pub decoder: DecoderConfig,
     pub text_encoder: t5::Config,
     pub vocab_size: usize,
+    pub audio_encoder: crate::models::dac::Config,
 }
 
 #[derive(Debug, Clone)]
@@ -325,6 +326,7 @@ pub struct Model {
     pub text_encoder: t5::T5EncoderModel,
     pub decoder_start_token_id: u32,
     pub pad_token_id: u32,
+    pub audio_encoder: crate::models::dac::Model,
 }
 
 impl Model {
@@ -347,6 +349,8 @@ impl Model {
         } else {
             None
         };
+        let audio_encoder =
+            crate::models::dac::Model::new(&cfg.audio_encoder, vb.pp("audio_encoder"))?;
         Ok(Self {
             decoder,
             text_encoder,
@@ -354,6 +358,7 @@ impl Model {
             enc_to_dec_proj,
             decoder_start_token_id: cfg.decoder_start_token_id,
             pad_token_id: cfg.pad_token_id,
+            audio_encoder,
         })
     }