Create README.md

README.md

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+# Token Awareness Dataset
+Built from "strawberry" meme 🍓, most LLM can't count the character of the word. Since this dataset is very easy to generate, we create a dataset for this benchmark just for fun.
+
+For this dataset, we support only Thai (th) and English (en) language.
+
+## Dataset Creation
+We sample words for each language from these sources:
+- Thai: [pythainlp's Thai words](https://github.com/PyThaiNLP/pythainlp/blob/dev/pythainlp/corpus/words_th.txt)
+- English: [dwyl's English words](https://github.com/dwyl/english-words/blob/master/words_alpha.txt)
+
+We then sample 500 word each weigted by the word score, which was computed using this simple heuristic:
+$$
+S(w) = \frac{\sqrt{|w|}}{\frac{1}{|w|} \sum_{i=1}^{|w|-1} \text{freq}(u_i) + \sum_{j=1}^{|w|-2} \text{freq}(b_j)}
+$$
+
+where:
+- $|w|$ is the length of the word.
+- $u_i$ represents the unigram (single character) in the word.
+- $b_j$ represents the bigram (pair of consecutive characters) in the word.
+- $\text{freq}(u_i)$ is the frequency of unigram $u_i$ in the overall corpus.
+- $\text{freq}(b_j)$ is the frequency of bigram $b_j$ in the overall corpus.
+
+we use a random seed of 42.
+
+## Author
+Chompakorn Chaksangchaichot