FineTuning AutoModelForSequenceClassification.from_pretrained(meta-llama/Llama-3.2-1B) Bug:RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:1 and cuda:0! (when checking argument for argument target in method wrapper_CUDA_nll_loss_forward) and awq importing

[alestrami]

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Fixes # (issue)

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I added two contributions.

1. The first one regarding the mismatch about the batch of the devices then training the model with the attribute device_map='auto'. Discussed here for AutoModelForSequenceClassification.from_pretrained. Thasnks to [hust] who provided the solution. Working also in my case with llama 3.3 1B https://discuss.huggingface.co/t/fine-tune-meta-llama-llama-2-7b-hf-bug-expected-all-tensors-to-be-on-the-same-device-but-found-at-least-two-devices-cuda-1-and-cuda-0-when-checking-argument-for-argument-target-in-method-wrapper-cuda-nll-loss-forward/129341/1
2. The seconds is regarding the checking of availability of the package awq for loading quantized models. 'problems importing in awq # importlib.metadata.version doesn't work with awq (line 144 src/transformers/utils/import_utils.py) . mportlib.metadata.version(pkg_name) works with 'autoawq' and not 'awq' while importlib.util.find_spec("awq") works only with awq and not autoawq. Both of thems need to be taken into account (is the same package)