add model

app.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from voxify import VoxifyInfereence
+from Voxify import VoxifyInfereence
 import torchaudio
 voxify=VoxifyInfereence(name="declare-lab/TangoFlux")
 def gradio_generate(prompt, steps, guidance,duration=10):

requirements..txt

@@ -1,11 +1,11 @@
-torch==2.4.0
-torchaudio===2.4.0
-torchlibrosa==0.1.0
-torchvision==0.19.0
-transformers==4.44.0
-diffusers==0.32.0
-accelerate==0.34.2
-datasets==2.21.0
+torch
+torchaudio
+torchlibrosa
+torchvision
+transformers
+diffusers
+accelerate
+datasets
 librosa
 tqdm
-wavio==0.0.7
+wavio

voxify.py

@@ -1,7 +1,5 @@
-import torch
 from diffusers import AutoencoderOobleck
-from torch import nn
-import numpy as np
+import torch
 from model import Voxify
 from huggingface_hub import snapshot_download
 from safetensors.torch import load_file
@@ -13,8 +11,8 @@ class VoxifyInfereence:
         weights=load_file("{}/tangoflux.safetensors".format(path))
         with open("{}/config.json".format(path), "r") as f:
             config = json.load(f)
-            self.voxify = Voxify(config)
-            self.voxify.load_state_dict(weights,strict=False)
+            self.model = Voxify(config)
+            self.model.load_state_dict(weights,strict=False)
     def generate(self, prompt,steps=25,duration=10,guidance_scale=4.5):
         with torch.no_grad():
             latent=self.model.inference_flow(prompt,