Package: llm-weights-mmap
llm_weights_mmapInstallationpipinstallllm_weights_mmapWhat is itThe script is designed to read.pth(PyTorch model state dictionary) files from a given directory and dump each key in the.pthfile to a separate.npy(NumPy array) file in an output directory.Why use it:Selective Loading: The script allows you to extract specific keys (i.e., layers or parameters) from a.pthfile, so you can load only the portions of the model that you're interested in.Memory Efficiency: The script enables you to load individual keys one at a time, offering a more memory-efficient way to inspect or manipulate model weights, especially when working with large models that might otherwise consume a significant amount of memory.DependenciesnumpytorchUsageRun the script from the command line and specify the.pthfiles directory and the output directory:python-mllm_weights_mmap.weights_separation--input/path/to/pth_files_dir--output/path/to/output_dirExampleSuppose you have a bunch of.pthfiles in a directory:➜lsllama-2-13b
checklist.chkconsolidated.00.pthconsolidated.01.pthparams.jsonRun the script this way:python-mllm_weights_mmap.weights_separation--inputllama-2-13b--outputllama-2-13b-separatedOutput:└──llama-2-13b├──consolidated.00│├──layers.0.attention_norm.weight.npy│├──layers.0.attention.wk.weight.npy│├──layers.0.attention.wo.weight.npy│├──layers.0.attention.wq.weight.npy│├──layers.0.attention.wv.weight.npy│├──layers.0.feed_forward.w1.weight.npy│├──layers.0.feed_forward.w2.weight.npy│├──layers.0.feed_forward.w3.weight.npy│├──layers.0.ffn_norm.weight.npy│├──layers.10.attention_norm.weight.npy│├──layers.10.attention.wk.weight.npy│├──layers.10.attention.wo.weight.npy│├──layers.10.attention.wq.weight.npy│├──layers.10.attention.wv.weight.npy│├──layers.10.feed_forward.w1.weight.npy│├──layers.10.feed_forward.w2.weight.npy│├──layers.10.feed_forward.w3.weight.npy│├──layers.10.ffn_norm.weight.npy│├──layers.11.attention_norm.weight.npy│├──layers.11.attention.wk.weight.npy│├──layers.11.attention.wo.weight.npy│├──layers.11.attention.wq.weight.npy│├──layers.11.attention.wv.weight.npy│├──layers.11.feed_forward.w1.weight.npy│├──layers.11.feed_forward.w2.weight.npy│├──layers.11.feed_forward.w3.weight.npy│├──layers.11.ffn_norm.weight.npy│├──layers.12.attention_norm.weight.npy│├──layers.12.attention.wk.weight.npy│├──layers.12.attention.wo.weight.npy│├──layers.12.attention.wq.weight.npy│├──layers.12.attention.wv.weight.npy│├──layers.12.feed_forward.w1.weight.npy│├──layers.12.feed_forward.w2.weight.npy│├──layers.12.feed_forward.w3.weight.npy│├──layers.12.ffn_norm.weight.npy│├──layers.13.attention_norm.weight.npy│├──layers.13.attention.wk.weight.npy│├──layers.13.attention.wo.weight.npy│├──layers.13.attention.wq.weight.npy│├──layers.13.attention.wv.weight.npy│├──layers.13.feed_forward.w1.weight.npy│├──layers.13.feed_forward.w2.weight.npy│├──layers.13.feed_forward.w3.weight.npy│├──layers.13.ffn_norm.weight.npy│├──layers.14.attention_norm.weight.npy│├──layers.14.attention.wk.weight.npy│├──layers.14.attention.wo.weight.npy│├──layers.14.attention.wq.weight.npy│├──layers.14.attention.wv.weight.npy│├──layers.14.feed_forward.w1.weight.npy│├──layers.14.feed_forward.w2.weight.npy│├──layers.14.feed_forward.w3.weight.npy│├──layers.14.ffn_norm.weight.npy│├──layers.15.attention_norm.weight.npy│├──layers.15.attention.wk.weight.npy│├──layers.15.attention.wo.weight.npy│├──layers.15.attention.wq.weight.npy│├──layers.15.attention.wv.weight.npy│├──layers.15.feed_forward.w1.weight.npy│├──layers.15.feed_forward.w2.weight.npy│├──layers.15.feed_forward.w3.weight.npy│├──layers.15.ffn_norm.weight.npy│├──layers.16.attention_norm.weight.npy│├──layers.16.attention.wk.weight.npy│├──layers.16.attention.wo.weight.npy│├──layers.16.attention.wq.weight.npy│├──layers.16.attention.wv.weight.npy│├──layers.16.feed_forward.w1.weight.npy│├──layers.16.feed_forward.w2.weight.npy│├──layers.16.feed_forward.w3.weight.npy│├──layers.16.ffn_norm.weight.npy│├──layers.17.attention_norm.weight.npy│├──layers.17.attention.wk.weight.npy│├──layers.17.attention.wo.weight.npy│├──layers.17.attention.wq.weight.npy│├──layers.17.attention.wv.weight.npy│├──layers.17.feed_forward.w1.weight.npy│├──layers.17.feed_forward.w2.weight.npy│├──layers.17.feed_forward.w3.weight.npy│├──layers.17.ffn_norm.weight.npy│├──layers.18.attention_norm.weight.npy│├──layers.18.attention.wk.weight.npy│├──layers.18.attention.wo.weight.npy│├──layers.18.attention.wq.weight.npy│├──layers.18.attention.wv.weight.npy│├──layers.18.feed_forward.w1.weight.npy│├──layers.18.feed_forward.w2.weight.npy│├──layers.18.feed_forward.w3.weight.npy│├──layers.18.ffn_norm.weight.npy│├──layers.19.attention_norm.weight.npy│├──layers.19.attention.wk.weight.npy│├──layers.19.attention.wo.weight.npy│├──layers.19.attention.wq.weight.npy│├──layers.19.attention.wv.weight.npy│├──layers.19.feed_forward.w1.weight.npy│├──layers.19.feed_forward.w2.weight.npy│├──layers.19.feed_forward.w3.weight.npy│├──layers.19.ffn_norm.weight.npy│├──layers.1.attention_norm.weight.npy│├──layers.1.attention.wk.weight.npy│├──layers.1.attention.wo.weight.npy│├──layers.1.attention.wq.weight.npy│├──layers.1.attention.wv.weight.npy│├──layers.1.feed_forward.w1.weight.npy│├──layers.1.feed_forward.w2.weight.npy│├──layers.1.feed_forward.w3.weight.npy│├──layers.1.ffn_norm.weight.npy│├──layers.20.attention_norm.weight.npy│├──layers.20.attention.wk.weight.npy│├──layers.20.attention.wo.weight.npy│├──layers.20.attention.wq.weight.npy│├──layers.20.attention.wv.weight.npy│├──layers.20.feed_forward.w1.weight.npy│├──layers.20.feed_forward.w2.weight.npy│├──layers.20.feed_forward.w3.weight.npy│├──layers.20.ffn_norm.weight.npy│├──layers.21.attention_norm.weight.npy│├──layers.21.attention.wk.weight.npy│├──layers.21.attention.wo.weight.npy│├──layers.21.attention.wq.weight.npy│├──layers.21.attention.wv.weight.npy│├──layers.21.feed_forward.w1.weight.npy│├──layers.21.feed_forward.w2.weight.npy│├──layers.21.feed_forward.w3.weight.npy│├──layers.21.ffn_norm.weight.npy│├──layers.22.attention_norm.weight.npy│├──layers.22.attention.wk.weight.npy│├──layers.22.attention.wo.weight.npy│├──layers.2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