Comments (2)
Can also try to get a pooled version of each predicted token vector based on the regular Tito Joker model, and another model that generates only positive statements. This new model should be a language model fine tuned on positive examples of a sentiment analysis dataset.
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OpenAI published exactly how to do the above with IMDB reviews!!
Interesting to see that the tag controls are quite similar to ours, the main difference seems to be the use of an additional reward function
for the sentiment special tokens.
https://lvwerra.github.io/trl/05-gpt2-sentiment-control/
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Related Issues (20)
- Create raw jokes sample in data dir for testing purposes
- Add preprocessing CLI usage to README
- Bias generated output based entities found in the input
- [experiment] Apply generation techniques employed from “abstractive summarization” and “Answer generation from Q&A augmentation” HOT 7
- Deploy Tito Joker V2 by updating streamlit app
- Tito Joker v2 sometimes returns answers missing the last letter HOT 2
- Create Tito Joker API with FastAPI
- Create TIto Joker twitter account and post jokes daily
- Initialize tests for the tito_joker module
- Include model version as a column in the feedback file
- Refactor `run_generation` module HOT 5
- Apply conditional joke reconstruction with the inclusion of tokens in the answer
- Integrate pun generation HOT 1
- Add custom context to control "topic" of answer
- Apply emotion control to text generation
- how to run HOT 2
- Style transfer for standup comedy
- Generate full standup comedy transcripts
- Resurrect hosted version please. I got "ValueError: Connection error" when trying to run locally
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