train.py script crashes when using HQQ

Here's the command I ran:

```
python train.py \
--model_name meta-llama/Llama-2-70b-hf \
--batch_size 1 \
--context_length 1024 \
--precision bf16 \
--train_type hqq_lora \
--use_gradient_checkpointing true \
--use_cpu_offload false \
--dataset alpaca \
--reentrant_checkpointing true \
--log_to wandb \
--gradient_accumulation_steps 8 \
--lr_scheduler linear \
--verbose false \
--lora_rank 16 \
--no_sync true
```

this crashes with the stack trace:

```
Creating model 0
Loading model 0
Loading & Quantizing Model Shards: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 15/15 [03:02<00:00, 12.18s/it]
Model created 0 0.067 GB
LoRA layers added 0 0.067 GB
Wrapping model w/ FSDP 0
Traceback (most recent call last):
File "/home/alyssa/lm_fun/fsdp_qlora/train.py", line 953, in
def main(
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/fastcore/script.py", line 125, in call_parse
return _f()
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/fastcore/script.py", line 119, in _f
return tfunc(**merge(args, args_from_prog(func, xtra)))
File "/home/alyssa/lm_fun/fsdp_qlora/train.py", line 1026, in main
mp.spawn(fsdp_main,
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/torch/multiprocessing/spawn.py", line 241, in spawn
return start_processes(fn, args, nprocs, join, daemon, start_method="spawn")
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/torch/multiprocessing/spawn.py", line 197, in start_processes
while not context.join():
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/torch/multiprocessing/spawn.py", line 158, in join
raise ProcessRaisedException(msg, error_index, failed_process.pid)
torch.multiprocessing.spawn.ProcessRaisedException:

-- Process 1 terminated with the following error:
Traceback (most recent call last):
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/torch/multiprocessing/spawn.py", line 68, in _wrap
fn(i, *args)
File "/home/alyssa/lm_fun/fsdp_qlora/train.py", line 703, in fsdp_main
model = FSDP(
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py", line 477, in __init__
_auto_wrap(
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/torch/distributed/fsdp/_wrap_utils.py", line 101, in _auto_wrap
_recursive_wrap(**recursive_wrap_kwargs, **root_kwargs) # type: ignore[arg-type]
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/torch/distributed/fsdp/wrap.py", line 543, in _recursive_wrap
wrapped_child, num_wrapped_params = _recursive_wrap(
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/torch/distributed/fsdp/wrap.py", line 543, in _recursive_wrap
wrapped_child, num_wrapped_params = _recursive_wrap(
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/torch/distributed/fsdp/wrap.py", line 543, in _recursive_wrap
wrapped_child, num_wrapped_params = _recursive_wrap(
[Previous line repeated 1 more time]
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/torch/distributed/fsdp/wrap.py", line 561, in _recursive_wrap
return _wrap(module, wrapper_cls, **kwargs), nonwrapped_numel
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/torch/distributed/fsdp/wrap.py", line 490, in _wrap
return wrapper_cls(module, **kwargs)
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py", line 503, in __init__
_init_param_handle_from_module(
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/torch/distributed/fsdp/_init_utils.py", line 548, in _init_param_handle_from_module
_materialize_with_param_init_fn(
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/torch/distributed/fsdp/_init_utils.py", line 851, in _materialize_with_param_init_fn
param_init_fn(module)
File "/home/alyssa/lm_fun/fsdp_qlora/train.py", line 713, in
param_init_fn=lambda module: module.to_empty(device=torch.device("cuda"), recurse=False)
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/hqq/core/quantize.py", line 485, in to_empty
return self.cuda(device)
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/hqq/core/quantize.py", line 419, in cuda
self.W_q.data, self.meta = Quantizer.cuda(self.W_q.data, self.meta, device)
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/hqq/core/quantize.py", line 220, in cuda
return Quantizer.to_inplace(W_q, meta, device=device)
File "/home/alyssa/anaconda3/envs/lm_fun/lib/python3.10/site-packages/hqq/core/quantize.py", line 181, in to_inplace
W_q = W_q.to(device).contiguous()
NotImplementedError: Cannot copy out of meta tensor; no data!

```

Start in train.py at fsdp_main around lines 703 and 713, then reproduce the reported command to inspect the FSDP initialization failure. Trace the interaction with HQQ shown in the stack trace; done means the HQQ training path completes FSDP wrapping without the reported meta-tensor crash.

Written by the indexing model from the issue text.