CUSTOM
CLANKERS.
← Browse all models

Doctor-Shotgun / Model details

Qwen3-Coder-30B-A3B-Instruct-ScatterMoE

Doctor-Shotgun/Qwen3-Coder-30B-A3B-Instruct-ScatterMoE

fine-tuned
Download files on Hugging Face ↗

Read the original model card ↗ · Choosing a model

About this model

Doctor-Shotgun's repository repackages Qwen/Qwen3-Coder-30B-A3B-Instruct weights using Charles Goddard's remote code implementation of scattermoe. The model card describes it as a drop-in replacement for efficient training with any transformers-based training repository, and includes scripts to convert to and from standard Qwen3MoeForCausalLM. Optional monkeypatches for Liger Kernel and Cut Cross-Entropy are also included. The weights are provided in safetensors format under an Apache-2.0 license. The creator does not describe this as fine-tuning or merging; it is a weight re-packing for training efficiency.

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/Qwen3-Coder-30B-A3B-Instruct
Parameters
30.5321B
Main repository formats
safetensors
License tag
apache-2.0
Languages
Unknown
Last updated
2025-08-01 · 19:35:15.000 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/Qwen3-Coder-30B-A3B-Instruct

Family evidence

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

  • Qwen: Base model: Qwen/Qwen3-Coder-30B-A3B-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/doctor-shotgun-qwen3-coder-30b-a3b-instruct-scattermoe/)

HTML

<a href="https://customclankers.com/models/doctor-shotgun-qwen3-coder-30b-a3b-instruct-scattermoe/">Listed on Custom Clankers</a>

Plain text links only: no image, no script, nothing loaded from this site.

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

  • Heretic ↗ ★ 36,553

    Removes refusal behavior from transformer models automatically. It pairs directional ablation (abliteration) with an Optuna parameter search that tries to cut refusals while keeping the model close to the original, so you don't have to pick layers by hand.

  • OBLITERATUS ↗ ★ 8,966

    A larger refusal-removal toolkit with several abliteration methods, usable locally or through a hosted Hugging Face Space. Check the telemetry setting before you run it: the README describes telemetry as opt-in, but on by default in the Spaces version.

Fine-tune it on your own data

  • Unsloth ↗ ★ 78,592

    A desktop app and Python library for running and training models locally. Its README lists LoRA, QLoRA, full fine-tuning, DPO and GRPO, plus export to formats including GGUF, on Windows, Linux, WSL and macOS.

  • LlamaFactory ↗ ★ 75,742

    Fine-tunes more than 100 language and vision-language models from a command line or a browser-based Web UI, aimed at training without writing code.

Make a smaller download (quantize)

  • llama.cpp ↗ ★ 132,430

    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 ↗ ★ 7,479

    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 ↗ ★ 7,418

    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 ↗ ★ 84,721

    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.

Compare all tools →

Source provenance

Downloads
37
Likes
1
Metadata checked
2026-10-26 · 16:11:04 UTC
First seen in index
2026-10-26 · 16:11:04 UTC
Source revision
2d9e23e2726632fc38cc24a3e95005bf773db20f

Source-card excerpt

Source model card excerpt: Qwen3-Coder-30B-A3B-Instruct-ScatterMoE Re-packed weights of Qwen/Qwen3-Coder-30B-A3B-Instruct using Charles Goddard's remote code implementation of scattermoe, including scripts to convert to and from standard Qwen3MoeForCausalLM . Thank

From Doctor-Shotgun/Qwen3-Coder-30B-A3B-Instruct-ScatterMoE. 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 ↗