say offline.page uses v2

README.md

@@ -77,13 +77,13 @@ model-index:
 
 <br>
 
-tinynext is the autocomplete in [offline.page](https://github.com/cfahlgren1/offline-page). It's the same model as [`cfahlgren1/enron-autocomplete`](https://huggingface.co/cfahlgren1/enron-autocomplete), copied here under its new name.
+tinynext is the autocomplete in [offline.page](https://github.com/cfahlgren1/offline-page). The app uses **v2**, in [`v2/`](https://huggingface.co/cfahlgren1/tinynext/tree/main/v2). The files at the root are v1, the original character model, the same as [`cfahlgren1/enron-autocomplete`](https://huggingface.co/cfahlgren1/enron-autocomplete).
 
 ## v2: the next few words, with context
 
 <sub>In [`v2/`](https://huggingface.co/cfahlgren1/tinynext/tree/main/v2). The files at the root of this repo are still v1.</sub>
 
-v1 guesses one letter at a time, so its suggestions are short word endings. v2 is a **12.5M-parameter transformer that predicts word pieces**, so one step can be a whole word, and it reads up to about 1,500 characters before the cursor (and, when there is any, text after it). It runs in a Web Worker in offline.page: add `?autocomplete=v2` to try it.
+v1 guesses one letter at a time, so its suggestions are short word endings. v2 is a **12.5M-parameter transformer that predicts word pieces**, so one step can be a whole word, and it reads up to about 1,500 characters before the cursor (and, when there is any, text after it). It's the autocomplete in offline.page, running in a Web Worker.
 
 **How much typing it saves.** Every model is scored by [`v2/eval.py`](v2/eval.py) on the same held-out text: type it character by character, pause every 12 characters, and count a suggestion only if the text really continues that way. Same decoding rule and 50% cutoff as the app, suggestions of 4+ characters.