ConicCat/Qwen3.5-27B-Writer-V2
A tentative second version. Hopefully, it's better.
A writing & roleplay finetune of Qwen3.5 27B. The primary emphasis is on writing quality as it strongly generalizes across both domains.
The basic idea is to use a curriculum learning setup to overcome the lack of high quality roleplay data by first training on lower quality roleplay data, then training on higher quality writing data. Starting from ConicCat/Qwen3.5-Antirep-27B, the model was trained on a roughly equal mixture of instruct / roleplay / writing data for three epochs. The model was then trained for eleven epochs on a smaller dataset of book chunks.
Recommended Settings
- Chatml template with
<think>\n\n</think>\nprefill or<think>\nprefill. Should think less! - temperature =
0.7 - top_p =
0.95 - A moderate dry penalty of ~
0.4-0.8should work well. - For quants, Q4_K_M runs well with
~100kcontext on 24GB Vram - IQ4_XS should fit on 16GB Vram with about
20-24kcontext with the vulkan backend, although it's pretty tight and may require some fiddling around with open programs e.t.c.
Datasets
ConicCat/AntiRep to mitigate repetitition.
internlm/Condor-SFT-20K for instruct; even though instruct capabilities are not the primary focus, adding some instruct data helps mitigate forgetting and maintains general intellect and instruction following capabilites.
ConicCat/Gutenberg-SFT. A reformatted version of the original Gutenberg DPO dataset by jondurbin for SFT with some slight augmentation to address many of the samples being overly long.
ConicCat/MiniC2_V3.2. The venerable C2, with cleaned and reformatted system prompts, and all user / assistant turns replaced by V3.2.
A dataset of backtranslated books. Unfortunately, I am unable to release this set as all of the data is under copyright.