how to use transformers with float16

[chaowenguo1]

import transformers, torch, builtins, numpy

processor = transformers.AutoProcessor.from_pretrained(' facebook/musicgen-stereo-melody-large', torch_dtype=torch.float16)
model = transformers.MusicgenMelodyForConditionalGeneration.from_pretrained('facebook/musicgen-stereo-melody-large ,torch_dtype=torch.float16).to('cuda')

result = []
for _ in builtins.range(2):
    inputs = processor(audio=result[-1] if result else None, sampling_rate=model.config.audio_encoder.sampling_rate, text='A grand and majestic symphony with soaring strings, powerful brass, and dynamic orchestration. Inspired by Beethoven and Tchaikovsky, featuring dramatic crescendos, delicate woodwind passages, and a triumphant finale. The mood is epic, emotional, and timeless', padding=True, return_tensors='pt').to('cuda')
    audio_values = model.generate(**inputs, max_new_tokens=1000)
    result += audio_values[0, 0].cpu().numpy(),

from IPython.display import Audio
Audio(numpy.concatenate(result), rate=model.config.audio_encoder.sampling_rate)

i always get

<ipython-input-12-348220656bb8> in <cell line: 0>()
      7 for _ in builtins.range(2):
      8     inputs = processor(audio=torch.from_numpy(result[-1]).to(dtype=torch.float32) if result else None, sampling_rate=model.config.audio_encoder.sampling_rate, text='A grand and majestic symphony with soaring strings, powerful brass, and dynamic orchestration. Inspired by Beethoven and Tchaikovsky, featuring dramatic crescendos, delicate woodwind passages, and a triumphant finale. The mood is epic, emotional, and timeless', padding=True, return_tensors='pt').to('cuda')
----> 9     audio_values = model.generate(**inputs, max_new_tokens=1000)
     10     result += audio_values[0, 0].cpu().numpy(),
     11 

5 frames
/usr/local/lib/python3.11/dist-packages/torch/nn/modules/linear.py in forward(self, input)
    123 
    124     def forward(self, input: Tensor) -> Tensor:
--> 125         return F.linear(input, self.weight, self.bias)
    126 
    127     def extra_repr(self) -> str:

RuntimeError: mat1 and mat2 must have the same dtype, but got Float and Half```