This is the model used for knowledge cluster classification for the DSTC10 track2 knowledge selection task, trained with double heads, i.e., classifier head and LM head

For further information, please refer to https://github.com/yctam/dstc10_track2_task2 for the Github repository. This model is used  to predict knowledge clusters under noisey dialogues generated by speech recognition errors\\

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{"language": "en", "tags": ["dp2"], "widget": [{"text": "oh and we'll mi thing uh is there bike clo ars or bike crac where i can park my thee"}, {"text": "oh and one more thing uhhh is there bike lockers or a bike rack where i can park my bike"}, {"text": "ni yeah that sounds great ummm dold you have the any idea er could you check for me if there's hat three wifie available there"}, {"text": "nice yeah that sounds great ummm do you have any idea or could you check for me if there's uhhh free wi-fi available there"}, {"text": "perfect and what is the check kin time for that"}]}
transformers pytorch bert text-classification dp2 en autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #dp2 #en #autotrain_compatible #endpoints_compatible #region-us 

This is the model used for knowledge cluster classification for the DSTC10 track2 knowledge selection task, trained with double heads, i.e., classifier head and LM head

For further information, please refer to URL for the Github repository. This model is used  to predict knowledge clusters under noisey dialogues generated by speech recognition errors\\

---
TAGS
#transformers #pytorch #bert #text-classification #dp2 #en #autotrain_compatible #endpoints_compatible #region-us 
