Update README.md

README.md

@@ -6,17 +6,17 @@ library_name: transformers
 tags:
 - mergekit
 - merge
-
+license: gemma
 ---
 # Gemma-2-Ataraxy-9B
 
 This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
 
-My favorite Gemma 2 9B models are the SPPO iter3 and SimPO finetunes, but I felt the slerp merge between the two (nephilim v3) wasn't as good for some reason. Another of my favorites, the Gutenberg Gemma 2 finetune by nbeerbower is another my favorites. It's trained on one of my favorite datasets, and actually improves the SPPO model's average openllm leaderboard 2 average score by a bit, on top of improving it's writing capabilities and making the LLM sound less AI-like. However I still like the original SPPO finetune a bit more, I think because the gutenberg finetune may have been slightly overfit on the gutenberg dataset. 
+My favorite Gemma 2 9B models are the SPPO iter3 and SimPO finetunes, but I felt the slerp merge between the two (nephilim v3) wasn't as good for some reason. The Gutenberg Gemma 2 finetune by nbeerbower is another my favorites. It's trained on one of my favorite datasets, and actually improves the SPPO model's average openllm leaderboard 2 average score by a bit, on top of improving it's writing capabilities and making the LLM sound less AI-like. However I still like the original SPPO finetune a bit more, I think because the gutenberg finetune may have been slightly overfit on the gutenberg dataset. 
 
-Someone suggested that merging the base model on top of the gutenberg may help with the overfitting, which gave me a (possibly) better idea; slerp merging the SimPO finetune on top of the Gutenberg finetune, which is similar to the pretty popular Nephilim v3 recipe, using the Gutenberg finetune in place of the SPPO model, which may, in my opinion give us better results since Gutenberg was trained on top of SPPO. 
+Someone suggested that merging the base model on top of the gutenberg may help with the overfitting, which gave me a (possibly) better idea; slerp merging the SimPO finetune on top of the Gutenberg finetune, which is similar to the pretty popular Nephilim v3 recipe, using the Gutenberg finetune in place of the SPPO model, which I thought may give us better results since Gutenberg was trained on top of SPPO. 
 
-I wasn't entirely too sure, since if nephilim v3 is anything to go buy, it was probably going to also end up worse than the parent models. Normally when I try merges like these, they dont go anywhere, I'm pretty picky, and very skeptical usually, so most times I find that the merge is usually just not better than the original models or only marginally better. Tried this merge anyways to see how it goes, and much to my surprise, this time, I feel like I got very good results so figured I'd share, and hopefully this wont be just me introducing more useless slop into a world that already has way too many unnecessary merges. 
+I wasn't entirely too sure, since if nephilim v3 is anything to go buy, it was probably going to also end up worse than the parent models. Normally when I try merges like these, they dont go anywhere. I'm pretty picky, and very skeptical usually, so most times I find that the merge is usually just not better than the original models or only marginally better. Tried this merge anyways to see how it goes, and much to my surprise, this time, I feel like I got very good results. Figured I'd share, and hopefully this wont be just me introducing more useless slop into a world that already has way too many unnecessary merges. 
 
 If you're looking for a mistral nemo 12B model instead, I HIGHLY recommend Mistral Nemo Gutenberg v2 by nbeerbower. It's head and shoulders above the many other mistral nemo finetunes I've tried (romulus simpo and magnum mini 1.1 being close second favorites).
 
@@ -52,4 +52,4 @@ slices:
     model: princeton-nlp/gemma-2-9b-it-SimPO
   - layer_range: [0, 42]
     model: nbeerbower/gemma2-gutenberg-9B
-```
+```