diff --git a/sbv2_core/src/model.rs b/sbv2_core/src/model.rs
deleted file mode 100644
index 603ea83..0000000
--- a/sbv2_core/src/model.rs
+++ /dev/null
@@ -1,90 +0,0 @@
-use crate::error::Result;
-use ndarray::{array, Array1, Array2, Array3, Axis, Ix3};
-use ort::{GraphOptimizationLevel, Session};
-
-#[allow(clippy::vec_init_then_push, unused_variables)]
-pub fn load_model<P: AsRef<[u8]>>(model_file: P, bert: bool) -> Result<Session> {
-    let mut exp = Vec::new();
-    #[cfg(feature = "tensorrt")]
-    {
-        if bert {
-            exp.push(
-                ort::TensorRTExecutionProvider::default()
-                    .with_fp16(true)
-                    .with_profile_min_shapes("input_ids:1x1,attention_mask:1x1")
-                    .with_profile_max_shapes("input_ids:1x100,attention_mask:1x100")
-                    .with_profile_opt_shapes("input_ids:1x25,attention_mask:1x25")
-                    .build(),
-            );
-        }
-    }
-    #[cfg(feature = "cuda")]
-    {
-        #[allow(unused_mut)]
-        let mut cuda = ort::CUDAExecutionProvider::default()
-            .with_conv_algorithm_search(ort::CUDAExecutionProviderCuDNNConvAlgoSearch::Default);
-        #[cfg(feature = "cuda_tf32")]
-        {
-            cuda = cuda.with_tf32(true);
-        }
-        exp.push(cuda.build());
-    }
-    #[cfg(feature = "directml")]
-    {
-        exp.push(ort::DirectMLExecutionProvider::default().build());
-    }
-    #[cfg(feature = "coreml")]
-    {
-        exp.push(ort::CoreMLExecutionProvider::default().build());
-    }
-    exp.push(ort::CPUExecutionProvider::default().build());
-    Ok(Session::builder()?
-        .with_execution_providers(exp)?
-        .with_optimization_level(GraphOptimizationLevel::Level3)?
-        .with_intra_threads(num_cpus::get_physical())?
-        .with_parallel_execution(true)?
-        .with_inter_threads(num_cpus::get_physical())?
-        .commit_from_memory(model_file.as_ref())?)
-}
-
-#[allow(clippy::too_many_arguments)]
-pub fn synthesize(
-    session: &Session,
-    bert_ori: Array2<f32>,
-    x_tst: Array1<i64>,
-    sid: Array1<i64>,
-    tones: Array1<i64>,
-    lang_ids: Array1<i64>,
-    style_vector: Array1<f32>,
-    sdp_ratio: f32,
-    length_scale: f32,
-    noise_scale: f32,
-    noise_scale_w: f32,
-) -> Result<Array3<f32>> {
-    let bert = bert_ori.insert_axis(Axis(0));
-    let x_tst_lengths: Array1<i64> = array![x_tst.shape()[0] as i64];
-    let x_tst = x_tst.insert_axis(Axis(0));
-    let lang_ids = lang_ids.insert_axis(Axis(0));
-    let tones = tones.insert_axis(Axis(0));
-    let style_vector = style_vector.insert_axis(Axis(0));
-    let outputs = session.run(ort::inputs! {
-        "x_tst" => x_tst,
-        "x_tst_lengths" => x_tst_lengths,
-        "sid" => sid,
-        "tones" => tones,
-        "language" => lang_ids,
-        "bert" => bert,
-        "style_vec" => style_vector,
-        "sdp_ratio" => array![sdp_ratio],
-        "length_scale" => array![length_scale],
-        "noise_scale" => array![noise_scale],
-        "noise_scale_w" => array![noise_scale_w]
-    }?)?;
-
-    let audio_array = outputs["output"]
-        .try_extract_tensor::<f32>()?
-        .into_dimensionality::<Ix3>()?
-        .to_owned();
-
-    Ok(audio_array)
-}