torchtune's InstructTemplate is deprecated, affecting llm_pte_finetuning examples

[RdoubleA]

🐛 Describe the bug

Hello from torchtune! We've recently deprecated torchtune.data.InstructTemplate in meta-pytorch/torchtune#1895 in favor of the more general torchtune.data.PromptTemplate that can be used for both instruct and chat data. Another major change is that now the prompt template is defined in the tokenizer and has a different contract.

In executorch, InstructTemplate is used in the examples/llm_pte_finetuning code and defined in those configs. If a user installs torchtune nightlies or install the upcoming stable version 0.4.0 of torchtune and tries to run this example, then it will fail. These callsites should be refactored to use the new PromptTemplate class and the configs should be updated accordingly.

I can open a PR to fix this, but wanted to give the team a heads up.

Versions

Versions of relevant libraries:
[pip3] executorch==0.5.0a0+2c32bf3
[pip3] flake8==7.0.0
[pip3] numpy==1.21.3
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] optree==0.12.1
[pip3] pytorch-sphinx-theme==0.0.24
[pip3] pytorch-triton==3.1.0+cf34004b8a
[pip3] torch==2.6.0.dev20241019+cpu
[pip3] torchao==0.5.0
[pip3] torchao-nightly==2024.3.29
[pip3] torchaudio==2.5.0.dev20241019+cpu
[pip3] torchsr==1.0.4
[pip3] torchtune==0.0.0
[pip3] torchvision==0.20.0.dev20241019+cpu
[pip3] triton==3.1.0
[conda] blas 1.0 mkl
[conda] cuda-cudart 12.1.105 0 nvidia
[conda] cuda-cupti 12.1.105 0 nvidia
[conda] cuda-libraries 12.1.0 0 nvidia
[conda] cuda-nvrtc 12.1.105 0 nvidia
[conda] cuda-nvtx 12.1.105 0 nvidia
[conda] cuda-opencl 12.3.101 0 nvidia
[conda] cuda-runtime 12.1.0 0 nvidia
[conda] executorch 0.5.0a0+2c32bf3 pypi_0 pypi
[conda] libcublas 12.1.0.26 0 nvidia
[conda] libcufft 11.0.2.4 0 nvidia
[conda] libcurand 10.3.4.107 0 nvidia
[conda] libcusolver 11.4.4.55 0 nvidia
[conda] libcusparse 12.0.2.55 0 nvidia
[conda] libnvjitlink 12.1.105 0 nvidia
[conda] magma-cuda124 2.6.1 1 pytorch
[conda] mkl 2023.1.0 h213fc3f_46344
[conda] mkl-include 2024.2.0 pypi_0 pypi
[conda] mkl-static 2024.2.0 pypi_0 pypi
[conda] numpy 1.21.3 pypi_0 pypi
[conda] nvidia-cublas-cu12 12.4.5.8 pypi_0 pypi
[conda] nvidia-cuda-cupti-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-cuda-nvrtc-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-cuda-runtime-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-cudnn-cu12 9.1.0.70 pypi_0 pypi
[conda] nvidia-cufft-cu12 11.2.1.3 pypi_0 pypi
[conda] nvidia-curand-cu12 10.3.5.147 pypi_0 pypi
[conda] nvidia-cusolver-cu12 11.6.1.9 pypi_0 pypi
[conda] nvidia-cusparse-cu12 12.3.1.170 pypi_0 pypi
[conda] nvidia-nccl-cu12 2.21.5 pypi_0 pypi
[conda] nvidia-nvjitlink-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-nvtx-cu12 12.4.127 pypi_0 pypi
[conda] optree 0.12.1 pypi_0 pypi
[conda] pytorch-cuda 12.1 ha16c6d3_5 pytorch-nightly
[conda] pytorch-mutex 1.0 cuda pytorch-nightly
[conda] pytorch-sphinx-theme 0.0.24 dev_0
[conda] pytorch-triton 3.1.0+cf34004b8a pypi_0 pypi
[conda] torch 2.6.0.dev20241019+cpu pypi_0 pypi
[conda] torchao 0.5.0 pypi_0 pypi
[conda] torchao-nightly 2024.3.29 pypi_0 pypi
[conda] torchaudio 2.5.0.dev20241019+cpu pypi_0 pypi
[conda] torchsr 1.0.4 pypi_0 pypi
[conda] torchtune 0.0.0 pypi_0 pypi
[conda] torchvision 0.20.0.dev20241019+cpu pypi_0 pypi
[conda] triton 3.1.0 pypi_0 pypi