Comments (5)
I'd presume you're using colab, as this means you have the wrong version of fastai. You need to install with --upgrade
. Also you need to install with interp
as the README states.
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Using colab. Did upgrade fastai with
!pip install fastai --upgrade
and did
!pip install fastinference[interp] per README, same issue. Any ideas?
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Copy/pasted in a bunch of the code from this notebook and it worked! https://github.com/muellerzr/fastinference/blob/master/nbs/02_shap.interp.ipynb
Hopefully that's insightful! Congrats on the new release! Got the book on order!
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I didn't get an issue, did you make sure to restart your instance? (also updating the shap requirement, didn't realize I missed one) I did the following steps:
!pip install fastinference[interp] shap
!pip install fastai --upgrade
from fastinference.tabular import *
Also, I had nothing to do with Jeremy & Sylvain's book :)
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It worked! Thank you!
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Related Issues (20)
- TypeError: waterfall() got an unexpected keyword argument 'feature_names' HOT 5
- NameError: name 'cat_names' is not defined HOT 2
- Fastinfernce has no tabular attirbute HOT 8
- can't import fastinference.onnx HOT 4
- ONNX import error
- Torchvision models do not seem to support `dynamic_axes` in ONNX export HOT 1
- Embedding gradients not being computed for intrinsic attention
- New fastai inference API HOT 3
- ModuleAttributeError: 'SequentialRNN' object has no attribute 'intrinsic_attention' HOT 2
- TypeError: requires_grad_() takes 1 positional argument but 2 were given HOT 11
- The onnx-cpu extra is installing fastai2 HOT 1
- feature importance returns a ModuleAttributeError HOT 1
- Error importing interpretation module
- Fix ONNX issues
- pip install fastinference[interp] doesn't work HOT 3
- Testme
- Testme
- Remove package from results, alternative option
- Returning N top predictions HOT 2
- Can't run notebooks
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