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I saw a different type of knowledge intended to load in main.py, including emotion, topic, persona, etc, but I did not find datasets to generate this knowledge. Would you like to share these dataset with me? Like "go_emotions", "plm_knowledge/preprocess_wow_train.pkl" in Persona and "atomic/v4_atomic_all.csv".
The text was updated successfully, but these errors were encountered:
Hi!
Sorry for being late to reply to you. I can provide the data, but due to its large size, downloading from my server will take some time, so the update might not be ready until tomorrow or the day after. I will upload this portion of data as soon as possible and reorganize the code to keep it aligned with the paper.
If you have any other questions, feel free to ask!
Thanks for the reply. Since I don't have the WOW dataset to explore knowledge, I tried to run the ablation study experiment with Dailydialog, but without WOW knowledge in the "main.py", and I got the error "assert len(utters) % 2 == 1". I think this error also will occur in the generation task(--gen). I'm wondering if these datasets used in response generation need to be preprocessed.
I saw a different type of knowledge intended to load in main.py, including emotion, topic, persona, etc, but I did not find datasets to generate this knowledge. Would you like to share these dataset with me? Like "go_emotions", "plm_knowledge/preprocess_wow_train.pkl" in Persona and "atomic/v4_atomic_all.csv".
The text was updated successfully, but these errors were encountered: