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README.md

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 ---
-license: apache-2.0
+license: afl-3.0
+language:
+- ru
+library_name: transformers
+pipeline_tag: text2text-generation
+tags:
+- humor
+- T5
+- jokes-generation
 ---
+
+
+## Task
+Model create for jokes generation task on Russian language.
+Generate jokes from scratch is too difficult task. Too make it easier jokes was splitted into setup and punch pairs.
+Each setup can produce infinite number of punches so inspiration was also introduced,
+which means main idea (or main word) of punch for given setup. In the real world, jokes come in different qualities (bad, good, funny, ...).
+Therefore, in order for the models to distinguish them from each other, a mark was introduced. It ranges from 0 (not a joke) to 5 (golden joke).
+
+
+## Info
+Model trained using flax on huge dataset with jokes and anekdots on different tasks:
+1. Span masks (dataset size: 850K)
+2. Conditional generation: generate inspiration by given setup (dataset size: 230K)
+3. Conditional generation: generate punch by given setup and inspiration (dataset size: 240K)
+4. Conditional generation: generate mark by given setup and punch (dataset size: 200K)
+
+
+## Ethical considerations and risks
+Model is fine-tuned on a large corpus of humorous text data scraped from from websites/telegram channels with anecdotes, shortliners, jokes.
+Text was not filtered for explicit content or assessed for existing biases.
+As a result the model itself is potentially vulnerable to generating equivalently inappropriate content or replicating inherent biases
+in the underlying data.
+Please don't take it seriously.