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Use some kind of BERT model available through fairseq. These are made for language modelling and hence can be used as encoder for the model.
__Possible Challenges__:
- ~~How to adapt dictionary?~~…
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One of the dominant scenario for text is to use some pre-trained encoder (Roberta, BERT, XLMR etc) and attach task specific head on top of it (classification head, Language modeling head, POS tagging …
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- [x] Change name of VOC_DIR to DICT_DIR
- [x] make externably usable
- [x] Integrate into data generation pipeline
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Hi,
Thanks for your work! I appreciate all the documentation and uploading the models to 🤗 . It is really useful!
I am trying to use the srl-en-xlmr but it seems that the tokenizer is not upload…
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Hello,
I was trying to reproduce some of the experiments (related to tokenizer metrics) in the paper and I am getting slightly different values for the fertility and continuation metrics. I was won…
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when I run "python train.py --config config/wnut17_doc.y", I got below error message
```
2021-09-30 09:31:34,791 Model training base path: "resources/taggers/xlmr-first_10epoch_2batch_2accumulate_0.…
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Hi,
We are trying to reprodue the numbers reported in the XTREME paper for mBERT on XNLI and PAWS-X tasks quoted (https://arxiv.org/pdf/2003.11080.pdf) in Table 12 and Table 15.
The hyperp…
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Hi
Thank you awesome-align team for the nice tool and the demo. I am trying to use XML-R with your model instead of M-BERT. I get an error with this line:
**out_src = model(ids_src.unsqueeze(0), o…
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I was trying to run the evaluation script for cz and I got this error.
python evaluate_conll2009.py --scorer scorer_conll2009.pl --processor xlmr_ft_full_all/processor_config.json --model xlmr_ft_f…
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Thanks for your realease.
While I try to run the code, it loads the model to the GPU (approx 2GB for XLMR) then it run mostly on CPU (20 processes at 100%). Is this a thing when it try to decode us…