Comments (2)
Update: It works with "codegen-350M-mono"
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Yep, this line is the root cause:
download_and_convert_model.sh: line 9: 8 Killed python3 codegen_gptj_convert.py --code_model Salesforce/${MODEL} ${MODEL}-hf
While converting the model, it loads the original model and the new model into RAM at once, so for the 16B versions that uses... a lot of RAM ๐ฌ
Doing the conversion piecemeal (e.g. layer by layer) is possible but I'd need to look a bit more deeply into the exact format of the pytorch_model.bin
format.
Another option is that I could try to host preconverted versions somewhere; they're pretty big though:
1.4G codegen-350M-mono-1gpu
1.4G codegen-350M-mono-2gpu
1.4G codegen-350M-multi-1gpu
1.4G codegen-350M-multi-2gpu
11G codegen-2B-mono-1gpu
11G codegen-2B-mono-2gpu
11G codegen-2B-multi-1gpu
11G codegen-2B-multi-2gpu
27G codegen-6B-mono-1gpu
27G codegen-6B-mono-2gpu
27G codegen-6B-multi-1gpu
27G codegen-6B-multi-2gpu
60G codegen-16B-mono-1gpu
60G codegen-16B-mono-2gpu
60G codegen-16B-multi-1gpu
60G codegen-16B-multi-2gpu
I'll look into seeing what the options for doing that are.
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