Update with imatrix training dataset info

README.md

@@ -149,6 +149,18 @@ is unfortunately very frequent).
 * RAM: A lot of RAM is required to compute imatrix files. Example: 512 GB is just enough to compute 405B imatrix quants in Q8.
 * GPU: At least 8 GB of memory.
 
+### Dataset
+
+* You want to create a dataset that is around double the size of bartowski1182's imatrix dataset. Quality is far more important
+than size. If you don't mind long training times, you can make it massive, but if you go beyond 1 MB there will
+probably be diminishing returns.
+* Your imatrix dataset should contain the typical output the model would generate when used for the workload you plan on using
+the model for. If you plan on using the model as a programming assistant, your imatrix dataset should contain the typical code
+you would ask it to write. The same applies for language. Our dataset is mostly English. If one would use our imatrix models in
+a different language they will likely perform worse than static quants as only a very small portion of our imatrix training data
+is multilingual. We only have the resources to generate single generic imatrix quants so our imatrix dataset must contain examples
+of every common use-case of an LLM.
+
 ### Extra tips
 
 * Computing 405B imatrix quants in Q8 does not seem to have any noticeable quality impact compared to BF16, so to save on hardware