Update modeling_ltgbert.py

#1

When initializing LtgbertForTokenClassification several LayerNorms don't have weight or bias.

And when using transformers>=4.40, two Metaspace's in tokenizer.json need "prepend_scheme" as follows:

      {
        "type": "Metaspace",
        "replacement": "▁",
        "add_prefix_space": false,
        "prepend_scheme": "never"
      },
HPLT org

Hi, thank you very much for reporting these issues! I will look more into it next week. We're still discussing what to do about the Metaspace pretokenizer, its new behavior might silently break more things: https://huggingface.co/HPLT/hplt_bert_base_en/discussions/1

Thank you @davda54 for new tokenizer.json with https://huggingface.co/HPLT/hplt_bert_base_ja/commit/3ba81b4d5b8885c06c3a0c8f4c7feb79fefee1cb , well, how about modeling_ltgbert.py?

davda54 changed pull request status to merged
HPLT org

Hi, I'm really sorry that it took me so long! Thank you once again for your fix, it's now applied to the Japanese BERT as well as to other HPLT-BERT models :)

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