ft model

app.py

@@ -100,9 +100,9 @@ def get_duration(model_name, tab, mid_seq, continuation_state, instruments, drum
                  key_sig, mid, midi_events, reduce_cc_st, remap_track_channel, add_default_instr,
                  remove_empty_channels, seed, seed_rand, gen_events, temp, top_p, top_k, allow_cc):
     if "large" in model_name:
-        return gen_events // 10 + 10
+        return gen_events // 10 + 15
     else:
-        return gen_events // 20 + 10
+        return gen_events // 20 + 15
 
 
 @spaces.GPU(duration=get_duration)
@@ -110,7 +110,7 @@ def run(model_name, tab, mid_seq, continuation_state, instruments, drum_kit, bpm
         reduce_cc_st, remap_track_channel, add_default_instr, remove_empty_channels, seed, seed_rand,
         gen_events, temp, top_p, top_k, allow_cc):
     model = models[model_name]
-    model.to(device=opt.device, dtype=torch.bfloat16 if opt.device == "cuda" else torch.float32).eval()
+    model.to(device=opt.device)
     tokenizer = model.tokenizer
     bpm = int(bpm)
     if time_sig == "auto":
@@ -302,8 +302,8 @@ if __name__ == "__main__":
                    "generic pretrain model (tv2o-large) by asigalov61": ["asigalov61/Music-Llama", "", "tv2o-large"],
                    "generic pretrain model (tv2o-medium) by asigalov61": ["asigalov61/Music-Llama-Medium", "", "tv2o-medium"],
                    "generic pretrain model (tv1-medium) by skytnt": ["skytnt/midi-model", "", "tv1-medium"],
-                   "j-pop finetune model (tv1-medium) by skytnt": ["skytnt/midi-model-ft", "jpop/", "tv1-medium"],
-                   "touhou finetune model (tv1-medium) by skytnt": ["skytnt/midi-model-ft", "touhou/", "tv1-medium"],
+                   "j-pop finetune model (tv2o-medium) by skytnt": ["skytnt/midi-model-ft", "jpop-tv2o-medium/", "tv2o-medium"],
+                   "touhou finetune model (tv2o-medium) by skytnt": ["skytnt/midi-model-ft", "touhou-tv2o-medium/", "tv2o-medium"],
                    }
     models = {}
     if opt.device == "cuda":
@@ -315,6 +315,7 @@ if __name__ == "__main__":
         ckpt = torch.load(model_path, map_location="cpu", weights_only=True)
         state_dict = ckpt.get("state_dict", ckpt)
         model.load_state_dict(state_dict, strict=False)
+        model.to(device="cpu", dtype=torch.bfloat16 if opt.device == "cuda" else torch.float32)
         models[name] = model
 
     load_javascript()