projecte-aina

/

aguila-7b

like 54

Hello!

I'm trying to deploy this model on AWS SageMaker by following the steps provided in the documentation. However, I'm encountering some errors during the endpoint creation process. I've double-checked my configurations, but the issues persist.

If anyone has experience deploying this model on AWS SageMaker or any insights into resolving similar errors, I'd greatly appreciate your help. Thanks in advance for any assistance you can offer!

Errors:

Error: DownloadError
    utils.convert_files(local_pt_files, local_st_files)
  File "/opt/conda/lib/python3.9/site-packages/text_generation_server/utils/convert.py", line 84, in convert_files
    convert_file(pt_file, sf_file)
  File "/opt/conda/lib/python3.9/site-packages/text_generation_server/utils/convert.py", line 62, in convert_file
    save_file(pt_state, str(sf_file), metadata={
    "format": "pt"
})
  File "/opt/conda/lib/python3.9/site-packages/safetensors/torch.py", line 232, in save_file
    serialize_file(_flatten(tensors), filename, metadata=metadata)
  File "/opt/conda/lib/python3.9/site-packages/safetensors/torch.py", line 394, in _flatten
    raise RuntimeError(

And the following error:

RuntimeError: 
            Some tensors share memory, this will lead to duplicate memory on disk and potential differences when loading them again: [{'transformer.h.6.mlp.dense_4h_to_h.weight', 'transformer.h.26.mlp.dense_4h_to_h.weight', 'transformer.h.4.self_attention.query_key_value.weight', 'transformer.h.22.mlp.dense_h_to_4h.weight', 'transformer.h.23.mlp.dense_h_to_4h.weight', 'transformer.h.5.mlp.dense_h_to_4h.weight', 'transformer.h.25.mlp.dense_h_to_4h.weight', 'transformer.h.25.mlp.dense_4h_to_h.weight', 'transformer.h.0.mlp.dense_4h_to_h.weight', 'transformer.h.11.mlp.dense_h_to_4h.weight', 'transformer.h.29.self_attention.dense.weight', 'transformer.h.24.self_attention.query_key_value.weight', 'transformer.h.24.mlp.dense_h_to_4h.weight', 'transformer.h.14.mlp.dense_4h_to_h.weight', 'transformer.h.1.self_attention.dense.weight', 'transformer.h.13.mlp.dense_4h_to_h.weight', 'transformer.h.8.self_attention.query_key_value.weight', 'transformer.h.20.self_attention.query_key_value.weight', 'transformer.h.27.mlp.dense_h_to_4h.weight', 'transformer.h.22.self_attention.query_key_value.weight', 'transformer.h.11.self_attention.query_key_value.weight', 'transformer.h.23.self_attention.query_key_value.weight', 'transformer.h.13.self_attention.dense.weight', 'transformer.h.15.mlp.dense_h_to_4h.weight', 'transformer.h.9.mlp.dense_h_to_4h.weight', 'transformer.h.15.self_attention.query_key_value.weight', 'transformer.h.24.mlp.dense_4h_to_h.weight', 'transformer.h.31.self_attention.query_key_value.weight', 'transformer.h.7.self_attention.dense.weight', 'transformer.h.27.self_attention.query_key_value.weight', 'transformer.h.1.mlp.dense_h_to_4h.weight', 'transformer.h.21.mlp.dense_4h_to_h.weight', 'transformer.h.24.self_attention.dense.weight', 'transformer.h.16.mlp.dense_4h_to_h.weight', 'transformer.h.20.mlp.dense_4h_to_h.weight', 'transformer.h.27.self_attention.dense.weight', 'transformer.h.4.mlp.dense_4h_to_h.weight', 'transformer.h.3.mlp.dense_h_to_4h.weight', 'transformer.h.25.self_attention.dense.weight', 'transformer.h.7.mlp.dense_4h_to_h.weight', 'transformer.h.17.self_attention.query_key_value.weight', 'transformer.h.19.self_attention.dense.weight', 'transformer.h.12.self_attention.query_key_value.weight', 'transformer.h.3.self_attention.dense.weight', 'transformer.h.28.mlp.dense_h_to_4h.weight', 'transformer.h.19.mlp.dense_h_to_4h.weight', 'transformer.h.20.self_attention.dense.weight', 'transformer.h.14.self_attention.query_key_value.weight', 'transformer.h.21.mlp.dense_h_to_4h.weight', 'transformer.h.12.mlp.dense_h_to_4h.weight', 'transformer.h.29.mlp.dense_h_to_4h.weight', 'transformer.h.6.mlp.dense_h_to_4h.weight', 'transformer.h.14.mlp.dense_h_to_4h.weight', 'transformer.h.30.self_attention.dense.weight', 'transformer.h.10.self_attention.query_key_value.weight', 'transformer.h.6.self_attention.query_key_value.weight', 'transformer.h.10.mlp.dense_4h_to_h.weight', 'transformer.h.23.mlp.dense_4h_to_h.weight', 'transformer.h.21.self_attention.query_key_value.weight', 'transformer.h.30.self_attention.query_key_value.weight', 'transformer.h.8.mlp.dense_h_to_4h.weight', 'transformer.h.30.mlp.dense_h_to_4h.weight', 'transformer.h.18.self_attention.query_key_value.weight', 'transformer.h.5.mlp.dense_4h_to_h.weight', 'transformer.h.15.mlp.dense_4h_to_h.weight', 'transformer.h.26.self_attention.dense.weight', 'transformer.h.9.self_attention.query_key_value.weight', 'transformer.h.17.mlp.dense_4h_to_h.weight', 'transformer.h.10.mlp.dense_h_to_4h.weight', 'transformer.h.6.self_attention.dense.weight', 'transformer.h.2.mlp.dense_4h_to_h.weight', 'transformer.h.5.self_attention.dense.weight', 'transformer.h.9.mlp.dense_4h_to_h.weight', 'transformer.h.3.mlp.dense_4h_to_h.weight', 'transformer.h.17.mlp.dense_h_to_4h.weight', 'transformer.h.27.mlp.dense_4h_to_h.weight', 'transformer.h.29.self_attention.query_key_value.weight', 'transformer.h.5.self_attention.query_key_value.weight', 'transformer.h.11.self_attention.dense.weight', 'transformer.h.19.mlp.dense_4h_to_h.weight', 'transformer.h.16.mlp.dense_h_to_4h.weight', 'transformer.h.8.mlp.dense_4h_to_h.weight', 'transformer.h.30.mlp.dense_4h_to_h.weight', 'transformer.h.31.mlp.dense_h_to_4h.weight', 'transformer.h.1.mlp.dense_4h_to_h.weight', 'transformer.h.28.self_attention.dense.weight', 'transformer.h.22.mlp.dense_4h_to_h.weight', 'transformer.h.31.self_attention.dense.weight', 'transformer.h.4.mlp.dense_h_to_4h.weight', 'transformer.h.19.self_attention.query_key_value.weight', 'transformer.h.0.self_attention.dense.weight', 'transformer.h.1.self_attention.query_key_value.weight', 'transformer.h.17.self_attention.dense.weight', 'transformer.h.18.self_attention.dense.weight', 'transformer.h.23.self_attention.dense.weight', 'transformer.h.28.self_attention.query_key_value.weight', 'transformer.h.12.mlp.dense_4h_to_h.weight', 'transformer.h.16.self_attention.query_key_value.weight', 'transformer.h.22.self_attention.dense.weight', 'transformer.h.18.mlp.dense_4h_to_h.weight', 'transformer.h.2.self_attention.query_key_value.weight', 'transformer.h.18.mlp.dense_h_to_4h.weight', 'transformer.h.8.self_attention.dense.weight', 'transformer.h.12.self_attention.dense.weight', 'transformer.h.29.mlp.dense_4h_to_h.weight', 'transformer.h.10.self_attention.dense.weight', 'transformer.h.26.mlp.dense_h_to_4h.weight', 'transformer.h.31.mlp.dense_4h_to_h.weight', 'transformer.h.3.self_attention.query_key_value.weight', 'transformer.h.16.self_attention.dense.weight', 'transformer.h.9.self_attention.dense.weight', 'transformer.h.21.self_attention.dense.weight', 'transformer.h.0.self_attention.query_key_value.weight', 'transformer.h.28.mlp.dense_4h_to_h.weight', 'transformer.word_embeddings.weight', 'transformer.h.0.mlp.dense_h_to_4h.weight', 'transformer.h.4.self_attention.dense.weight', 'transformer.h.13.self_attention.query_key_value.weight', 'transformer.h.7.mlp.dense_h_to_4h.weight', 'transformer.h.2.mlp.dense_h_to_4h.weight', 'transformer.h.7.self_attention.query_key_value.weight', 'transformer.h.11.mlp.dense_4h_to_h.weight', 'transformer.h.2.self_attention.dense.weight', 'transformer.h.13.mlp.dense_h_to_4h.weight', 'transformer.h.14.self_attention.dense.weight', 'transformer.h.15.self_attention.dense.weight', 'transformer.h.25.self_attention.query_key_value.weight', 'transformer.h.26.self_attention.query_key_value.weight', 'transformer.h.20.mlp.dense_h_to_4h.weight'}, {'transformer.h.22.input_layernorm.bias', 'transformer.h.17.input_layernorm.bias', 'transformer.h.20.input_layernorm.weight', 'transformer.h.20.input_layernorm.bias', 'transformer.h.1.input_layernorm.bias', 'transformer.h.18.input_layernorm.bias', 'transformer.h.28.input_layernorm.bias', 'transformer.h.7.input_layernorm.bias', 'transformer.h.5.input_layernorm.weight', 'transformer.h.8.input_layernorm.weight', 'transformer.h.0.input_layernorm.weight', 'transformer.h.9.input_layernorm.bias', 'transformer.h.12.input_layernorm.weight', 'transformer.h.19.input_layernorm.weight', 'transformer.h.30.input_layernorm.bias', 'transformer.h.31.input_layernorm.weight', 'transformer.h.6.input_layernorm.bias', 'transformer.h.7.input_layernorm.weight', 'transformer.h.6.input_layernorm.weight', 'transformer.ln_f.weight', 'transformer.h.5.input_layernorm.bias', 'transformer.h.13.input_layernorm.weight', 'transformer.h.13.input_layernorm.bias', 'transformer.h.30.input_layernorm.weight', 'transformer.h.19.input_layernorm.bias', 'transformer.h.18.input_layernorm.weight', 'transformer.h.16.input_layernorm.bias', 'transformer.h.27.input_layernorm.bias', 'transformer.h.21.input_layernorm.weight', 'transformer.h.14.input_layernorm.weight', 'transformer.h.16.input_layernorm.weight', 'transformer.h.10.input_layernorm.bias', 'transformer.h.25.input_layernorm.bias', 'transformer.h.23.input_layernorm.bias', 'transformer.h.29.input_layernorm.weight', 'transformer.h.11.input_layernorm.weight', 'transformer.h.3.input_layernorm.bias', 'transformer.ln_f.bias', 'transformer.h.22.input_layernorm.weight', 'transformer.h.28.input_layernorm.weight', 'transformer.h.0.input_layernorm.bias', 'transformer.h.1.input_layernorm.weight', 'transformer.h.14.input_layernorm.bias', 'transformer.h.24.input_layernorm.bias', 'transformer.h.8.input_layernorm.bias', 'transformer.h.21.input_layernorm.bias', 'transformer.h.10.input_layernorm.weight', 'transformer.h.12.input_layernorm.bias', 'transformer.h.27.input_layernorm.weight', 'transformer.h.31.input_layernorm.bias', 'transformer.h.11.input_layernorm.bias', 'transformer.h.23.input_layernorm.weight', 'transformer.h.26.input_layernorm.bias', 'transformer.h.29.input_layernorm.bias', 'transformer.h.15.input_layernorm.bias', 'transformer.h.2.input_layernorm.weight', 'transformer.h.2.input_layernorm.bias', 'transformer.h.24.input_layernorm.weight', 'transformer.h.4.input_layernorm.weight', 'transformer.h.26.input_layernorm.weight', 'transformer.h.15.input_layernorm.weight', 'transformer.h.4.input_layernorm.bias', 'transformer.h.9.input_layernorm.weight', 'transformer.h.25.input_layernorm.weight', 'transformer.h.3.input_layernorm.weight', 'transformer.h.17.input_layernorm.weight'}].
            A potential way to correctly save your model is to use `save_model`.
            More information at https://huggingface.co/docs/safetensors/torch_shared_tensors