Update README.md (#2)

- Update README.md (2bd97cdbb4b73334ce0557f68d9d92f6ab17d1d7)


Co-authored-by: Mikhail Arkhipov <mshny@users.noreply.huggingface.co>

README.md

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 # Dataset Summary
-The dataset contains 25000 Kotlin code samples selected from [KStack](https://huggingface.co/datasets/JetBrains/KStack) dataset. The selection is performed based on the value of the code for learning algorithmic concepts in Kotlin.
+The dataset contains 25000 Kotlin code samples selected from [KStack](https://huggingface.co/datasets/JetBrains/KStack) dataset. The selection is performed based on the value of the code for learning algorithmic concepts in Kotlin. In total, the dataset contains about 23M [CodeLlama-7b](https://huggingface.co/codellama/CodeLlama-7b-hf) tokens (vocab size 32016).
 
 # Dataset Collection Procedure
 The filtering is performed using zero-shot quality estimation based on [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2). The model is prompted to determine which of two files has higher "educational value for learning algorithms in Kotlin". The results of the comparisons are averaged and used to train a binary classifier based on [CodeT5p-220m](https://huggingface.co/Salesforce/codet5p-220m). The binary classifier is then applied to the entire KStack to obtain scores for each sample in the dataset. The log-probability of the classifier prediction used as a criterion of the selection.