Comments (3)
Thanks for reporting, I'll have a look.
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I did a quick fix, just import GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP and return GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP.keys() instead of GPT2LMHeadModel.pretrained_model_archive_map.keys()
from lm-scorer.
Fixed in v0.4.2.
Apparently they removed the pretrained_model_archive_map
in huggingface/transformers#4152.
Thanks for reporting!
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Related Issues (11)
- Unable to run lm-scorer HOT 1
- Python 3.8 support? HOT 5
- Can't load config for 'gpt2' HOT 5
- Not really correct to include <|endoftext|> token in scoring?
- Support for AutoModelWithLMHead
- Support for Python 3.8
- ValueError: Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' 'truncation=True' to have batched tensors with the same length. Perhaps your features (`input_ids` in this case) have excessive nesting (inputs type `list` where type `int` is expected).
- Possible missing words HOT 1
- Couple of queries: 1) Fine tuned GPT2 2) BPE Encoding HOT 2
- AH01215: OSError: Couldn't reach server at 'https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-config.json' to download pretrained model configuration file HOT 6
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