changes

generation_utilities.py

@@ -12,6 +12,7 @@ model_name = ["SAint7579/orpheus_ldm_model_v1-0", "teticio/audio-diffusion-ddim-
 
 audio_diffusion_v0 = AudioDiffusionPipeline.from_pretrained("teticio/latent-audio-diffusion-256").to(device)
 audio_diffusion_v1 = AudioDiffusionPipeline.from_pretrained("SAint7579/orpheus_ldm_model_v1-0").to(device)
+audio_diffusion_v2 = AudioDiffusionPipeline.from_pretrained("SAint7579/orpheus_ldm_model_v2-0").to(device)
 ddim = AudioDiffusionPipeline.from_pretrained("teticio/audio-diffusion-ddim-256").to(device)
 
 ### Add numpy docstring to generate_from_music
@@ -166,12 +167,14 @@ def generate_songs(conditioning_songs, similarity=0.9, quality=500, merging_qual
     # start = np.random.randint(0, len(merged) - 5 * sample_rate)
     # merged = merged[start:start + 5 * sample_rate]
 
-    if random.random() < 0.5:
-        diffuser = audio_diffusion_v0
-        model_name = "v0"
-    else:
-        diffuser = audio_diffusion_v1
-        model_name = "v1"
+
+
+    diffuser, model_name = random.choice([
+        (audio_diffusion_v0, "v0"),
+        (audio_diffusion_v1, "v1"),
+        (audio_diffusion_v2, "v2")
+    ])
+
     print("Generating song...")
     ## quality = X - similarity*X
     total_steps = min([1000, int(quality/(1-similarity))])