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bertscore-57537647.err
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==> WARNING: A newer version of conda exists. <==
current version: 23.5.2
latest version: 23.11.0
Please update conda by running
$ conda update -n base -c defaults conda
Or to minimize the number of packages updated during conda update use
conda install conda=23.11.0
WARNING: Ignoring invalid distribution -riton-nightly (/sfs/qumulo/qhome/brc4cb/.conda/envs/falcon_40B/lib/python3.9/site-packages)
Running command git clone --filter=blob:none --quiet https://github.com/huggingface/peft.git /tmp/pip-install-5givn0kh/peft_913fbc4d146c4bd2bdf1610c6951ba76
Running command git clone --filter=blob:none --quiet https://github.com/huggingface/accelerate.git /tmp/pip-install-5givn0kh/accelerate_1ed7dc5bcc7f4b508265d8c494b8dbf3
ERROR: Cannot install -r requirements.txt (line 2), -r requirements.txt (line 3), -r requirements.txt (line 6) and huggingface_hub==0.16.4 because these package versions have conflicting dependencies.
ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts
WARNING: Ignoring invalid distribution -riton-nightly (/sfs/qumulo/qhome/brc4cb/.conda/envs/falcon_40B/lib/python3.9/site-packages)
WARNING: Ignoring invalid distribution -riton-nightly (/sfs/qumulo/qhome/brc4cb/.conda/envs/falcon_40B/lib/python3.9/site-packages)
WARNING: Ignoring invalid distribution -riton-nightly (/sfs/qumulo/qhome/brc4cb/.conda/envs/falcon_40B/lib/python3.9/site-packages)
WARNING: Ignoring invalid distribution -riton-nightly (/sfs/qumulo/qhome/brc4cb/.conda/envs/falcon_40B/lib/python3.9/site-packages)
==> WARNING: A newer version of conda exists. <==
current version: 23.5.2
latest version: 23.11.0
Please update conda by running
$ conda update -n base -c defaults conda
Or to minimize the number of packages updated during conda update use
conda install conda=23.11.0
Some weights of RobertaModel were not initialized from the model checkpoint at roberta-large and are newly initialized: ['roberta.pooler.dense.bias', 'roberta.pooler.dense.weight']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.