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I'm unsure if this task should instead set feature_extractor, or just leave tokenizer as None.
Suggested fix
Instead of manually determining which tasks require feature_extractor or tokenizer, is it possible to process the full list of supported tasks from transformers, and then add the correct value based on the class structure? This will make the code much more future proof as transformers updates.
Add an environment variable to set the tokenizer. This way, if a similar error occurs in the future, developers can do a quick fix by overriding the value. (It may be worth noting that I am using a pre-built docker container, so I don't have the ability to modify this myself for a quick fix without doing a lot of other work. For this situation, an environment variable would be ideal.)
The text was updated successfully, but these errors were encountered:
When using the task type
image-text-to-text
, thetokenizer
is set toimage_url
, resulting inpipeline
being called withtokenizer
as a string. This causes an error withintransformers
.I'm unsure if this task should instead set
feature_extractor
, or just leavetokenizer
asNone
.Suggested fix
Instead of manually determining which tasks require
feature_extractor
ortokenizer
, is it possible to process the full list of supported tasks fromtransformers
, and then add the correct value based on the class structure? This will make the code much more future proof astransformers
updates.Add an environment variable to set the tokenizer. This way, if a similar error occurs in the future, developers can do a quick fix by overriding the value. (It may be worth noting that I am using a pre-built docker container, so I don't have the ability to modify this myself for a quick fix without doing a lot of other work. For this situation, an environment variable would be ideal.)
The text was updated successfully, but these errors were encountered: