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I hit this recently as well. I believe that the CoQA dataset only works with GPT-3, not with GPT-2. The problem is that:
1. CoQA uses a multi-token EOS marker. In coqa.py: rf.greedy_until(ctx, ['\nQ:'])
2. The harness only supports greedy_until(..) with a single token. All other callers only provide a single token, like '.' or a newline.
def greedy_until(self, requests):
# TODO: implement fully general `until` that handles untils that are
# multiple tokens or that span multiple tokens correctly
If you pass in a multi-token string, you get "ValueError: too many values to unpack (expected 1)". That's because only a single token is expected by the implementation.
3. GPT-3 uses a different implementation of greedy_until(..) that calls into the OpenAI APIs, and that seems to support multi-token greedy_until(..)
To confirm this, you can modify the call to rf.greedy_until(ctx, ['\nQ:']) in coqa.py to only pass in a single token, which will avoid the crashes, but presumably won't do the right thing as far as the benchmark is concerned.
So, to get CoQA working on GPT-2, a multi-token greedy_until will need to be implemented in base.py.
While running coqa task, i faced an error as follows
If I modify
primary_until, _
intoprimary_until
this generates another issueAny solutions ?
Thanks
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