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Comments (19)

chengchingwen avatar chengchingwen commented on June 11, 2024

Which version of Transformers.jl and Pickle.jl?

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rcherukuri12 avatar rcherukuri12 commented on June 11, 2024

(@v1.9) pkg> status Transformers
Status ~/.julia/environments/v1.9/Project.toml
Transformers v0.2.8
Pickle v0.3.2

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chengchingwen avatar chengchingwen commented on June 11, 2024

Ok, so you would need to update Pickle.jl to 0.3.3 which adds support for bfloat16.

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rcherukuri12 avatar rcherukuri12 commented on June 11, 2024

pkg>update Pickle
wouldn't do it.

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rcherukuri12 avatar rcherukuri12 commented on June 11, 2024

on linux / ubuntu ..is this platform specific ?

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chengchingwen avatar chengchingwen commented on June 11, 2024

Not really. What happens if you explicitly add [email protected]? I'm guessing there are some compat issues that block the update.

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rcherukuri12 avatar rcherukuri12 commented on June 11, 2024

(@v1.9) pkg> add [email protected]
Resolving package versions...
ERROR: Unsatisfiable requirements detected for package ReinforcementLearningZoo [d607f57d]:

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rcherukuri12 avatar rcherukuri12 commented on June 11, 2024

I will create a local project and activate and see if it works ..

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rcherukuri12 avatar rcherukuri12 commented on June 11, 2024

Similar warning as before ...
textenc = hgf"databricks/dolly-v2-12b:tokenizer"
┌ Warning: fuse_unk is unsupported, the tokenization result might be slightly different in some cases.
└ @ Transformers.HuggingFace ~/.julia/packages/Transformers/lD5nW/src/huggingface/tokenizer/utils.jl:42

will load the model and see if it works.

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rcherukuri12 avatar rcherukuri12 commented on June 11, 2024

This time ...no error , but model hangs ..
model = todevice(hgf"databricks/dolly-v2-12b":ForCausalLM")

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chengchingwen avatar chengchingwen commented on June 11, 2024

The warning can usually be ignored

model = todevice(hgf"databricks/dolly-v2-12b":ForCausalLM")

That is a big model, which takes time to be moved to GPU. And there is an extra ".

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rcherukuri12 avatar rcherukuri12 commented on June 11, 2024

I have a 3080 ti ..will wait to see and let you know . Thank you. I was able to run Ollama with other 13b models fairly quickly.

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rcherukuri12 avatar rcherukuri12 commented on June 11, 2024

finally it put out an error:
ERROR: LoadError: syntax: cannot juxtapose string literal

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chengchingwen avatar chengchingwen commented on June 11, 2024

That is because the extra "

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rcherukuri12 avatar rcherukuri12 commented on June 11, 2024

Let me see where it is happening ... it is this line:
model = todevice(hgf"databricks/dolly-v2-12b:ForCausalLM")

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rcherukuri12 avatar rcherukuri12 commented on June 11, 2024

The other thing , I noticed ..nvidia-smi was constant ...almost telling it was not copying there ..

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rcherukuri12 avatar rcherukuri12 commented on June 11, 2024

I will copy into a vim editor and try it out ..that way , double quotes sometimes comes up with special chars...that can be eliminated as a cause.

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rcherukuri12 avatar rcherukuri12 commented on June 11, 2024

Still no luck. It just kills my shell after a while . Will come back and try later .
For now I will stick to just using OpenAI.jl and continue my work.
Thank you for trying to help.

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chengchingwen avatar chengchingwen commented on June 11, 2024

It sounds like the process might be killed due to OOM.

So currently you would need about 70GB CPU memory to load the 12B model. This is actually larger than the size of model weights, due to our implementation detail. The model weight is directly copied from disk to memory, and during the construction of the model object, it makes another copy on CPU. So at the end it would take at least 2 times (or more, depending on the data type) larger memory than the size of model weights

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