
TL;DR: I publish GRP V2, which follows the same idea as GRP V1. This time, I used Mistral instead of Qwen2.5, because GRP V1 was good enough for its description; but I was sure I could squeeze out a bit more roleplaying; and there are a LOT of roleplaying models for Mistral. As a daily driver and professional envirments, it performs beyond expectation too ;)
Since that's what I do in my free-time, I don't get paid for it. Training stable models requires compute, you can help me buy more here ٩( ๑╹ ꇴ╹)۶
GRP V2 follows the same idea as V1, and the entire GRP series, basically: A daily-driver model with strong roleplaying abilities which would actually make it a "general" model; most models don't cover that, and if they do, they're usually highly censored. I intend to fix that.
Since I don't have a cluster to full-parameter fine-tune a model (I know of QLoRA, but stable uncensoring with good output isn't for LoRA), I merge models. Recycling n stuff.
For this merge, I browsed & tested ~17 models and ended up using five of them:
- Inv/Konstanta-V4-Alpha-7B: A really good model, exceptional roleplaying performance, yet struggles with causal assisting
- segolilylabs/Lily-Cybersecurity-7B-v0.2: A model for anything IT-related mainly, also strong reasoning abilities, only "good enough" for roleplaying though
- NeuralNovel/Panda-7B-v0.1: Again, good rp, good enough reasoning & assisting
- MaziyarPanahi/Mistral-7B-Instruct-Aya-101: Handles both roleplaying & assisting (in multiple languages!!) good enough
- NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story: Heavily roleplaying & well uncensored, used in hope of copying the non-existent alignment
In summary, I used a bit of everything. All models are licensed under Apache2.0, and are MistralV0.2 based. I didn't want to mess with multiple arch merging. I recommend the Mistral chat template, but, again, you can experiment.
Happy chatting!

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