Reputation: 51
conda by default installing transformers 2.x however pip installs 4.x by default which is what I want but via conda.
If I install by specifying the latest distribution file from conda-forge…
conda install https://anaconda.org/conda-forge/transformers/4.16.2/download/noarch/transformers-4.16.2-pyhd8ed1ab_0.tar.bz2
then it complains that environment is not consistent and list the package causing the issue which is PyTorch version 1.11.
I removed pytorch and then installed as listed above then installation go through. I then tried installing datasets…
conda install datasets
Now it complains that environment is inconsistent due to transformers 4.16.2 that I installed.
Not sure whats wrong and how to install pytorch, transformers and datasets together with no issue. Do I need specific versions of these to make it work, could not find any such guideline on huggingface docs or support pages.
thanks.
Upvotes: 5
Views: 12570
Reputation: 463
What worked for me is to download from conda-forge
channel instead of huggingface
channel, i.e.
conda install conda-forge::transformers
Upvotes: 0
Reputation: 13582
Just tried installing transformers in the venv
that I will be working on as follows
conda install transformers
And it installed the version transformers-4.18.0
.
If one wants to install specifically from the channel huggingface
, then do the following
conda install -c huggingface transformers
Last case scenario, install it with pip
, as using pip
can potentially wreck one's installation (pip
and conda
do not manage dependencies in the same way).
pip install transformers
Or, by specifying the version
pip install transformers==4.18.0
Or directly from the source
pip install git+https://github.com/huggingface/transformers
If one has transformers
already installed and wants to install a different version than the one we currently have, one should pass -Iv
(as suggested here)
pip install -Iv transformers==4.18.0
To check if transformers
was properly installed, run the following
python -c "from transformers import pipeline; print(pipeline('sentiment-analysis')('we love you'))"
It will download a pretrained model, then print out the label and score.
For more information on transformers
installation, consult this page.
Upvotes: 8