Comments (4)
MichalBrzozowski91
commented on June 18, 2024
Hi, thanks for feedback. Can you elaborate what is your use case? So far we have implemented support for longer sequences for the binary classification problem.
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rominaappierdo
commented on June 18, 2024
Thank you for your reply, I just wanted to know if there was a way to simply obtain embedding vectors. I would like to just obtain a representation vector for a given (longer) sequence, no need to perform downstream tasks currently. Is it possible to obtain them with your work?
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MichalBrzozowski91
commented on June 18, 2024
Hi, I was working on it and I think it is possible to obtain embedding vectors using our code. I created a PR with example notebook.
Feel free to ask any questions.
I hope it will help you.
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MichalBrzozowski91
commented on June 18, 2024
HI, we made major changes in this repo. Now in order to obtain embedding vectors, we suggest getting the tokenized chunks from the method _tokenize of the class BertClassifierWithPooling. The obtained tokens can then be directly fed to the pre-trained BERT to obtain embeddings of each chunk.
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Related Issues (16)
- QnA system using BERT HOT 2
- Any example colab scripts to fine tune BERT variations for text multi-class classification tasks? HOT 1
- Write description what does package do in Readme
- Outputting Attentions HOT 1
- running the fit function doesnt give me any verbose HOT 1
- use it for multiclass classification HOT 1
- Would it be okay to use the code below instead of bert? HOT 1
- text length warning HOT 2
- plz help me HOT 1
- Split Sizes Throws Error HOT 2
- A few general questions HOT 1
- RuntimeError with the following message: "mat1 and mat2 shapes cannot be multiplied (2x512 and 768x1) HOT 5
- Loss function and optimizer as parameters
- Managing GPU memory for token length more than 4000 HOT 1
- MaskedLM for longer texts HOT 1
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