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A notebook for question and answer generation using one of the most powerful opensource NLU models, FLAN-T5-11B. #215
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This is code that can be run in a notebook or by itself to generate a dictionary for use in creating synthetic dialogue that can be verified for factual accuracy. To use this notebook your need your trusted source material to be in the format of a list of strings (they will be truncated to under 1100 characters). Requires transformers and accelerate. Make sure to use T5 with bfloat16 or full precision.
could you a) run pre-commit to pass linting, and b) could you have a look at how the folder structure of |
Colab Link |
Moved to proper folder structure
I think it should be fixed now. I ran pre-commit and added the .md file and changed to have correct folder structure. Let me know if this works now. TwoDukes you may want to use the changes I put in. There was some whitespace problems and a few unused variables that were left over from other things I was doing before. I actually forgot incorporating the logits score was some custom code I wrote. I think I implemented it correctly, but someone else checking that may be helpful. |
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@Rallio67 pre-commit still reports problems, can you fix and give it another try? |
Whats the GPU VRAM requirements for the XXL model? |
You need a 24 gigabyte card and you need to use bfloat16. RTX3090 and other ampere level cards works with 24 gigabyte memory like the A10, A100, A5000 etc. |
This is code that can be run in a notebook or by itself to generate a dictionary for use in creating synthetic dialogue that can be verified for factual accuracy. To use this notebook your need your trusted source material to be in the format of a list of strings (they will be truncated to under 1100 characters). Requires transformers and accelerate. Make sure to use T5 with bfloat16 or full precision.
It would be nice if someone can convert this approach to work on colab. T5-11B should be able to run on TPU with colab.