Enabling Tapex in table question answering pipeline.
#16663
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| ) | ||
| self.type = "tapas" if hasattr(self.model.config, "aggregation_labels") else None |
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Wondering if we can leverage model.config.is_encoder_decoder here (which is True for TAPEX but False for TAPAS)
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Usually I would agree that reusing more "general" concepts is better.
The thing I want to avoid is treating not encoder-decoder as tapas. currently the code for Tapas is super highly specific, so I'd rather isolate tapas than isolate tapex if you want.
Ultimately both are OK tbh.
| if truncation is None: | ||
| if self.type == "tapas": | ||
| truncation = "drop_rows_to_fit" | ||
| else: | ||
| truncation = "do_not_truncate" |
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TAPEX also supports the "drop_rows_to_fit" truncation strategy.
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The tokenizer said it didn't and gave me the regular list.
Is the tokenizer that gets resolved a BartTokenizer maybe ? (I have seen BartTokenizer in some random error log, I discarded it, but maybe ti's a True bug.
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from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("microsoft/tapex-large-finetuned-wtq")
tokenizer.encode(table, truncation="drop_rows_to_fit")ValueError: drop_rows_to_fit is not a valid TruncationStrategy, please select one of ['only_first', 'only_second', 'longest_first', 'do_not_truncate']
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Thanks for reporting, investigating.
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Update: you can continue with this, TAPEX doesn't support drop_rows_to_fit in a similar manner as TAPAS does.
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The documentation is not available anymore as the PR was closed or merged. |
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Gentle ping @NielsRogge if we want to go live next week. |
…6663) * Enabling `Tapex` in table question answering pipeline. * Questions are independant for Tapex, making the test respect that. * Missing extra space.
What does this PR do?
Tapexmodels in the pipelineself.typeflag, sinceTapas(the previously used models)have some non trivial defaults which do not apply to
Tapex.(Ideally thosetypeare not model specific like
tapasbutencodervsencoder-decoderwhenapplicable.
model yet: https://huggingface.co/hf-internal-testing
@NielsRogge
@LysandreJik
Fixes # (issue)
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