UNITE version 10.0 is out, and I've built classifiers for it compatible with the newest version of Qiime2:
Eventually, this will be superseded when UNITE is provided directly on the Data Resources Page.
Not what you are looking for? Please send me a direct message or open an issue.
Colin 
Thank you very much Sir
I see "all" eukaryotes? Does this mean CO1?
Good question! I think UNITE is ITS only (so, no CO1 to my knowledge)
You can read more on their page: UNITE - Resources
Hello @colinbrislawn - I have a novice question about using this pre-trained classifier.
The qza files available in the GitHub link you posted, can these be used directly in the "test the classifier" portion of this q2-feature-classifier tutorial?
Ex:
qiime feature-classifier classify-sklearn
--i-classifier unite_ver9_dynamic_25.07.2023-Q2-2023.9.qza
--i-reads rep-seqs.qza
--o-classification taxonomy.qza
Hi @Taylor_Akers,
From what I understand, this should work!
Great, thank you @cherman2 ! It worked!
An off-topic reply has been split into a new topic: qiime2 does not recognize classifier as a .qza artifact
Please keep replies on-topic in the future.
Hi @colinbrislawn thank you for creating this classifier!
I downloaded the latest version and tried it with my data. However, it runs for about 20 minutes before the job is killed. I am assuming this is due to insufficient RAM (I have 16GB)?
In that case, I should likely create my own classifier using RESCRIPt? Thank you.
Making a new classifier takes more memory then using an existing classifier. Using one of these pre-made ones still probably your best option with limited memory...
I would try using a smaller number of reads per batch, say --p-reads-per-batch 5000 or 1000.
Also consider using a search based classifier like classify-consensus-blast: classify-consensus-blast: BLAST+ consensus taxonomy classifier — QIIME 2 2023.9.2 documentation