---
license: apache-2.0
datasets:
- ConicCat/Gutenberg-SFT
- ConicCat/AntiRep
- ConicCat/Condor-SFT-Filtered
- ConicCat/MiniC2_V3.2
base_model:
- Qwen/Qwen3.5-27B
---
# 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 `\n\n\n` prefill or `\n` prefill. Should think less!
* temperature = `0.7`
* top_p = `0.95`
* A moderate dry penalty of ~ `0.4-0.8` should work well.
* For quants, Q4_K_M runs well with `~100k` context on 24GB Vram
* IQ4_XS should fit on 16GB Vram with about `20-24k` context 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.