Comments (5)
Thanks for the note!
I don't use a Windows machine, but @jonthegeek does, so maybe he can give you some advice?
Just a heads up: we're working on a package that implements BERT using the "torch" R package. This should be a lot easier to install and maintain than the TensorFlow implementation. We hope to make this available before too long.
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That's great to hear. Yeah, I realized after I submitted this that this could be a version control issue with TensorFlow or something. But I think that the issue is something about how windows works with compilation--hence why it seems to be similar to the Stan problem I linked to.
Hopefully switching to Torch will get around that. Thanks again for the reply.
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For what it's worth, we don't do anything with withr and don't have any compiled code, so that particular error comes from something else. Do you have something about withr in your .Rprofile, maybe? I don't think this is a Windows thing, per se, but it COULD be from something you had to do to get stan to install.
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Oh yeah, that last remark I think is probably right. I had to alter my .Rprofile to get Stan's compilers to work. I suspect doing that messed with something here. Well, that's good to know. I'll try this from a clean install later and see if that works. I'll also mess around with withr and see if uninstalling that at least lets me install the package.
Thanks!
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So removing withr for installation was sufficient to install RBERT. Thanks again!
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Related Issues (20)
- extract_features by model name HOT 2
- Better use_one_hot_embeddings documentation in extract_features HOT 1
- Prompt to Install tensorflow HOT 1
- Share model List Between Functions HOT 2
- Speed Up `extract_features` HOT 5
- Save tokenizer as part of model HOT 1
- https://github.com/bnosac/golgotha HOT 7
- uniquify incoming text
- Rewrite and Speed Up Tokenizer HOT 1
- Move Tokenizer to Separate Package HOT 2
- Decide how to handle tokenization conventions
- (TF2) improve functions in functions-to-improve.R
- start using assert package for safety checks?
- figure out better way to pass token type ids to model
- figure out TF warning message
- change package tests to work with tiny BERT checkpoint
- DL of large model failed
- Error when running RBERT In Tensorflow 1.11.0: "Error in py_call_impl(callable, dots$args, dots$keywords)" HOT 1
- Not getting to download the bert_base_uncased HOT 3
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