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Datasets:
yujiepan
/
awq-model-zoo

Tags:
awq
llm
quantization
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The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    DataFilesNotFoundError
Message:      No (supported) data files found in yujiepan/awq-model-zoo
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 65, in compute_config_names_response
                  get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1840, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1821, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1215, in get_module
                  module_name, default_builder_kwargs = infer_module_for_data_files(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 591, in infer_module_for_data_files
                  raise DataFilesNotFoundError("No (supported) data files found" + (f" in {path}" if path else ""))
              datasets.exceptions.DataFilesNotFoundError: No (supported) data files found in yujiepan/awq-model-zoo

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yujiepan/awq-model-zoo

Here are some pre-computed awq information (scales & clips) used in llm-awq.

Scripts 

python do_awq.py --model_id mistralai/Mistral-7B-v0.1 --w_bit 8 --q_group_size 128 --dump_awq ./awq-info.pt
  • Load a quantized model: You can use the offical repo to get a fake/real quantized model. Alternatively, you can load a fake-quantized model:
from do_awq import FakeAWQModel
FakeAWQModel.from_pretrained('mistralai/Mistral-7B-v0.1', awq_meta_path='./awq-info.pt',  output_folder='./tmp/')

Note: the code is not in good shape.

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