Cannot use TTS

[gitzJess]

I have no idea how to fix it please help. I have trained my voice but I cannot use it.

Model training done!
C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\xtts_demo.py:437: FutureWarning: You are using torch.load with weights_only=False (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for weights_only will be flipped to True. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via torch.serialization.add_safe_globals. We recommend you start setting weights_only=True for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
checkpoint = torch.load(model_path, map_location=torch.device("cpu"))
Loading XTTS model!
C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\venv\lib\site-packages\TTS\tts\layers\xtts\xtts_manager.py:6: FutureWarning: You are using torch.load with weights_only=False (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for weights_only will be flipped to True. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via torch.serialization.add_safe_globals. We recommend you start setting weights_only=True for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
self.speakers = torch.load(speaker_file_path)
Traceback (most recent call last):
File "C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\venv\lib\site-packages\TTS\tts\models\xtts.py", line 782, in load_checkpoint
self.load_state_dict(checkpoint, strict=strict)
File "C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 2215, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for Xtts:
Missing key(s) in state_dict: "gpt.prompt_embedding.weight", "gpt.prompt_pos_embedding.emb.weight".
Unexpected key(s) in state_dict: "gpt.conditioning_perceiver.latents", "gpt.conditioning_perceiver.layers.0.0.to_q.weight", "gpt.conditioning_perceiver.layers.0.0.to_kv.weight", "gpt.conditioning_perceiver.layers.0.0.to_out.weight", "gpt.conditioning_perceiver.layers.0.1.0.weight", "gpt.conditioning_perceiver.layers.0.1.0.bias", "gpt.conditioning_perceiver.layers.0.1.2.weight", "gpt.conditioning_perceiver.layers.0.1.2.bias", "gpt.conditioning_perceiver.layers.1.0.to_q.weight", "gpt.conditioning_perceiver.layers.1.0.to_kv.weight", "gpt.conditioning_perceiver.layers.1.0.to_out.weight", "gpt.conditioning_perceiver.layers.1.1.0.weight", "gpt.conditioning_perceiver.layers.1.1.0.bias", "gpt.conditioning_perceiver.layers.1.1.2.weight", "gpt.conditioning_perceiver.layers.1.1.2.bias", "gpt.conditioning_perceiver.norm.gamma".
size mismatch for gpt.mel_embedding.weight: copying a param with shape torch.Size([1026, 1024]) from checkpoint, the shape in current model is torch.Size([8194, 1024]).
size mismatch for gpt.mel_head.weight: copying a param with shape torch.Size([1026, 1024]) from checkpoint, the shape in current model is torch.Size([8194, 1024]).
size mismatch for gpt.mel_head.bias: copying a param with shape torch.Size([1026]) from checkpoint, the shape in current model is torch.Size([8194]).

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\venv\lib\site-packages\gradio\queueing.py", line 536, in process_events
response = await route_utils.call_process_api(
File "C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\venv\lib\site-packages\gradio\route_utils.py", line 322, in call_process_api
output = await app.get_blocks().process_api(
File "C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\venv\lib\site-packages\gradio\blocks.py", line 1935, in process_api
result = await self.call_function(
File "C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\venv\lib\site-packages\gradio\blocks.py", line 1520, in call_function
prediction = await anyio.to_thread.run_sync( # type: ignore
File "C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\venv\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
return await get_async_backend().run_sync_in_worker_thread(
File "C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\venv\lib\site-packages\anyio_backends_asyncio.py", line 2405, in run_sync_in_worker_thread
return await future
File "C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\venv\lib\site-packages\anyio_backends_asyncio.py", line 914, in run
result = context.run(func, *args)
File "C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\venv\lib\site-packages\gradio\utils.py", line 826, in wrapper
response = f(*args, **kwargs)
File "C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\xtts_demo.py", line 53, in load_model
XTTS_MODEL.load_checkpoint(config, checkpoint_path=xtts_checkpoint, vocab_path=xtts_vocab,speaker_file_path=xtts_speaker, use_deepspeed=False)
File "C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\venv\lib\site-packages\TTS\tts\models\xtts.py", line 786, in load_checkpoint
self.load_state_dict(checkpoint, strict=strict)
File "C:\Users\ZJE\Documents\Artificial-Intelligence\Ultimate-TTS\xtts-finetune-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 2215, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for Xtts:
Missing key(s) in state_dict: "gpt.gpt.wte.weight", "gpt.prompt_embedding.weight", "gpt.prompt_pos_embedding.emb.weight", "gpt.gpt_inference.transformer.h.0.ln_1.weight", "gpt.gpt_inference.transformer.h.0.ln_1.bias", "gpt.gpt_inference.transformer.h.0.attn.c_attn.weight", "gpt.gpt_inference.transformer.h.0.attn.c_attn.bias", "gpt.gpt_inference.transformer.h.0.attn.c_proj.weight", "gpt.gpt_inference.transformer.h.0.attn.c_proj.bias", "gpt.gpt_inference.transformer.h.0.ln_2.weight", "gpt.gpt_inference.transformer.h.0.ln_2.bias", "gpt.gpt_inference.transformer.h.0.mlp.c_fc.weight", "gpt.gpt_inference.transformer.h.0.mlp.c_fc.bias", "gpt.gpt_inference.transformer.h.0.mlp.c_proj.weight", "gpt.gpt_inference.transformer.h.0.mlp.c_proj.bias", "gpt.gpt_inference.transformer.h.1.ln_1.weight", "gpt.gpt_inference.transformer.h.1.ln_1.bias", "gpt.gpt_inference.transformer.h.1.attn.c_attn.weight", "gpt.gpt_inference.transformer.h.1.attn.c_attn.bias", 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"gpt.gpt_inference.final_norm.weight", "gpt.gpt_inference.final_norm.bias", "gpt.gpt_inference.lm_head.0.weight", "gpt.gpt_inference.lm_head.0.bias", "gpt.gpt_inference.lm_head.1.weight", "gpt.gpt_inference.lm_head.1.bias".
Unexpected key(s) in state_dict: "gpt.conditioning_perceiver.latents", "gpt.conditioning_perceiver.layers.0.0.to_q.weight", "gpt.conditioning_perceiver.layers.0.0.to_kv.weight", "gpt.conditioning_perceiver.layers.0.0.to_out.weight", "gpt.conditioning_perceiver.layers.0.1.0.weight", "gpt.conditioning_perceiver.layers.0.1.0.bias", "gpt.conditioning_perceiver.layers.0.1.2.weight", "gpt.conditioning_perceiver.layers.0.1.2.bias", "gpt.conditioning_perceiver.layers.1.0.to_q.weight", "gpt.conditioning_perceiver.layers.1.0.to_kv.weight", "gpt.conditioning_perceiver.layers.1.0.to_out.weight", "gpt.conditioning_perceiver.layers.1.1.0.weight", "gpt.conditioning_perceiver.layers.1.1.0.bias", "gpt.conditioning_perceiver.layers.1.1.2.weight", "gpt.conditioning_perceiver.layers.1.1.2.bias", "gpt.conditioning_perceiver.norm.gamma".
size mismatch for gpt.mel_embedding.weight: copying a param with shape torch.Size([1026, 1024]) from checkpoint, the shape in current model is torch.Size([8194, 1024]).
size mismatch for gpt.mel_head.weight: copying a param with shape torch.Size([1026, 1024]) from checkpoint, the shape in current model is torch.Size([8194, 1024]).
size mismatch for gpt.mel_head.bias: copying a param with shape torch.Size([1026]) from checkpoint, the shape in current model is torch.Size([8194]).