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Sao10K / Model details

32B-Qwen2.5-Kunou-v1

Sao10K/32B-Qwen2.5-Kunou-v1

fine-tuned
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About this model

Sao10K's 32B-Qwen2.5-Kunou-v1 is a QLoRA-trained derivative of Qwen/Qwen2.5-32B-Instruct, released as safetensors weights under an 'other' license. The creator describes it as a generalist and roleplay model, made with a cleaned-up version of the datasets used for Euryale and Stheno, and calls it a kind-of successor to L3-70B-Euryale-v2.2 in all but name. The training configuration uses custom ChatML datasets for unalignment, roleplay/creative instruct, and Hesperus-v2 instruct data. The model card does not provide independent evaluations of these modified weights. Recommended settings from the creator are ChatML prompt format, temperature 1.1, and min_p 0.1.

Description sources

Source-based description, not an independent evaluation. Check the linked sources for the creator’s claims and limitations.

Size and formats

Base model
Qwen/Qwen2.5-32B-Instruct
Parameters
32.7639B
Main repository formats
safetensors
License tag
other
Languages
Unknown
Last updated
2024-12-30 · 02:37:59.000 UTC

What changed

Model types are creator-reported, not independently tested. These labels describe source metadata, not a guarantee of behavior.

  • fine-tunedsource tag: base_model:finetune:Qwen/Qwen2.5-32B-Instruct

Family evidence

These groupings are source-reported. Explicit base identifiers take priority over generic architecture tags.

  • Qwen: Base model: Qwen/Qwen2.5-32B-Instruct

Available versions

Versions appear here only when they explicitly name this exact model as their source. Check each repository for available files.

Link to this listing

Made or quantized this model? Paste one of these into your model card or README so people can find this listing.

Markdown

[Listed on Custom Clankers](https://customclankers.com/models/sao10k-32b-qwen2-5-kunou-v1/)

HTML

<a href="https://customclankers.com/models/sao10k-32b-qwen2-5-kunou-v1/">Listed on Custom Clankers</a>

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Customize or build on this model

Listed from public GitHub data, not tested by us. Read the code and license before you run anything.

Tools to customize it further

Remove more refusals

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Fine-tune it on your own data

  • Unsloth ↗ ★ 78,549

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Make a smaller download (quantize)

  • llama.cpp ↗ ★ 132,313

    Runs models locally and includes the tools behind most GGUF files. A conversion script turns Hugging Face weights into GGUF, and llama-quantize shrinks a high-precision GGUF to lower-bit formats, which can cost some accuracy.

  • MLX LM ↗ ★ 7,470

    Apple's MLX package for running and fine-tuning models on Apple silicon. It can quantize models and upload them to the Hugging Face Hub, and supports LoRA and full fine-tuning.

Merge it with another model

  • mergekit ↗ ★ 7,415

    Merges pretrained models with many merge methods. It works out-of-core, so merges can run on a CPU or with as little as 8 GB of VRAM, and it also handles LoRA extraction and mixture-of-experts merges.

Learn the techniques

  • LLM Course ↗ ★ 84,684

    A free course with roadmaps and Colab notebooks. Its notebooks include one-click tools for merging with MergeKit, quantizing to GGUF, GPTQ, EXL2, AWQ and HQQ, and automatic abliteration with custom datasets.

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Source provenance

Downloads
132
Likes
42
Metadata checked
2026-10-25 · 16:11:04 UTC
First seen in index
2026-10-25 · 16:11:04 UTC
Source revision
cc5c69b5eb30a2b62069bc7bea4cc08cacc0062c

Source-card excerpt

Source model card excerpt: Sister Versions for Lightweight and Heavyweight Use! 72B-Kunou-v1 14B-Kunou-v1 32B-Qwen2.5-Kunou-v1 training delays and all... I do not really have anything planned for this model

From Sao10K/32B-Qwen2.5-Kunou-v1. Creator model-card excerpt, not an independent review.

Inspect before you run

Low refusal is not proof of correctness. Outputs can be inaccurate, harmful, or biased. Review the model card, license and files yourself. A license tag is not commercial-use advice. Parameter counts are source metadata; no hardware compatibility is implied.

This directory does not host or redistribute model weights. Refusal profiles are measured by us on a fixed prompt set; all other behavior claims are source-reported.

Collection rules & limitations ↗