t5_config_yaml.py

yaml_config="""
input_features:
    -
        name: Original_Title
        type: text
        level: word
        encoder: t5
        reduce_output: null
    -
        name: Keyword
        type: text
        level: word
        tied_weights: Original_Title
        encoder: t5
        reduce_output: null

output_features:
    -
        name: Optimized_Title
        type: sequence
        level: word
        decoder: generator
"""

with open("config.yaml", "w") as f:
  f.write(yaml_config)

Yes. I did notice that too - the two files are different.

That's the reason why I changed it in my code and used Hamlet's updated YAML file:
https://gist.githubusercontent.com/hamletbatista/e0498d79dfef5350cec8171d8e4a1f03/raw/e012a235522773fca9d3543907193172232bb44f/ludwig_t5_config.yaml
(I have pasted the screenshots above)

My assumption is @shyamcody added these lines of code
from google.colab import files files.upload()

and uploaded the correct YAML file from his local folder/drive.

Regards,
Mithila K

Hi @mithila2806 I am also stuck at the same part as you with the error "ValueError: The following keyword arguments are not supported by this model: ['token_type_ids'].". Do you happen to have any update on the issue?

hey!

I didn't progress after that. Wil update here if at all I get lucky.

Thanks for your update 😊

Regards,
Mithila K

Hi again @mithila2806, the way I managed to avoid this error was by finding the python file were this error occured and comment out some lines. If I remember correctly the lines were 348,349,350,351. After doing that I run the model again end it worked. If you want me to explain anything else just hit me up!

hey @nearchoskatsanikakis

I was able to successfully run the code. I didn't do any changes. I simply ran the code and it worked:)
I believe there were some compatibility issues, which were fixed.

Happy coding 👍

Regards,
Mithila K

Great job @mithila2806 @nearchoskatsanikakis 👏🏽👏🏽👏🏽

I'm glad you got it to work!

Hi Hamlet

It wouldn't have been possible without you.
Can't thank you enough.
Regards,
Mithila

Hi Hamlet,

I'm getting issues when get to:

Import panda as pd

And

df = pd.read.csv("dAta.csv")

df.head ()

In the "data.csv" is that where I'm going to import my data I want to optimize?

And 2) How do I upload my data into it?

And after it has optimize the tag how do I download it into a spreadsheet for analysis?

@tthebimbolawal
When you dowload the file using the !wget instructions provided by Hamlet, the resulting csv will be named hootsuite_titles.csv, and it will be in the content folder, if you are using google-colab. See screenshot.
So, to load it in pandas you can do pd.read_csv('hootsuite_titles.csv')
I hope that answers your question.

Hello all,

Thank you all for the information.
I have followed all steps and tried to make it work.

When I run the following code,
!ludwig predict --dataset hootsuite_titles_to_optimize.csv --model_path results/experiment_run/model/

It returns this error
FileNotFoundError: [Errno 2] No such file or directory: 'results/experiment_run/model/model_hyperparameters.json'

Could you all tell me what model path I should use to make it work?
Thank you a lot

Hii while I am trying to replace hootsuite_titles.csv dataset with my website dataset I am getting a value error like this:
ValueError: A Concatenate layer requires inputs with matching shapes except for the concat axis. Got inputs shapes: [(128, 32, 512), (128, 224, 512)]
please reply.......

I believe you should try to avoid data sets with formulas in cells. Avoid cells with concatenate or other formulas and check file extension. I believe it must be CSV Marcus Bianco Lima Consultor de Marketing Digital (71) 991-129-175 Em qua., 8 de set. de 2021 02:25, Suvakanta8 ***@***.***> escreveu:

…

***@***.**** commented on this gist. ------------------------------ Hii while I am trying to replace hootsuite_titles.csv dataset with my website dataset I am getting a value error like this: ValueError: A Concatenate layer requires inputs with matching shapes except for the concat axis. Got inputs shapes: [(128, 32, 512), (128, 224, 512)] please reply....... — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <https://gist.github.com/1f9a86d4364f641f776808bff03f557b#gistcomment-3885902>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AP2OIIM6L5Q2WDZE5KBIUBLUA3XWLANCNFSM4UYMHB6Q> . Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub>.

Thanks @marcusbianco can you please explain me how to prepare a dataset properly for training and the optimized score column in hootsuit dataset what is that ? Is that necessary for training?

@marcusbianco While I am using this data set https://docs.google.com/spreadsheets/d/e/2PACX-1vQeg6komuBq6U4Rn_SWFNXgGxXIL4fhQcdJp2A8p0B2pmiucvDG5SUpXEGKooJPaTPsN0ivIaCvqIad/pub?gid=0&single=true&output=csv
its running fine but just check this dataset also https://docs.google.com/spreadsheets/d/e/2PACX-1vSbe_3C_JV06TQvL-TR741o7goEycu0oGwO3kfJleawuDQEQiu2ZC2lpgeHhRQayJ4JoZe6PvbdCvbF/pub?gid=0&single=true&output=csv , while I am trying to run this one its throwing that value error... please guide me.. Kindly check and tell me the differences..