mradermacher/Qwen35B-Agent-R2-Abliterated-i1-GGUF overview

---

base_model: hotdogs/Qwen35B-Agent-R2-Abliterated

datasets:

• hotdogs/uka-fable-reasoning
• 11-47/claude_opus_4.8_max_thinking_5k_v2
• cx-cmu/agent_trajectories

language:

• en
• th

library_name: transformers

license: agpl-3.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

• qwen
• moe
• mixture-of-experts
• agent
• agent-world
• tool-use
• tool-calling
• reasoning
• sft
• abliterated
• uncensored
• opus
• fable
• conversational
• vision
• image-text-to-text
• transformers
• text-generation
• thai
• ykai

---

About

<!-- ### quantize_version: 2 -->

<!-- ### output_tensor_quantised: 1 -->

<!-- ### convert_type: hf -->

<!-- ### vocab_type: -->

<!-- ### tags: nicoboss -->

<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->

<!-- ### quants_skip: -->

<!-- ### skip_mmproj: -->

weighted/imatrix quants of https://huggingface.co/hotdogs/Qwen35B-Agent-R2-Abliterated

<!-- provided-files -->

For a convenient overview and download list, visit our model page for this model.

static quants are available at https://huggingface.co/mradermacher/Qwen35B-Agent-R2-Abliterated-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of [TheBloke's

READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for

more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

| Link | Type | Size/GB | Notes |

|:-----|:-----|--------:|:------|

| GGUF | imatrix | 0.3 | imatrix file (for creating your own quants) |

| GGUF | i1-IQ1_S | 7.6 | for the desperate |

| GGUF | i1-IQ1_M | 8.3 | mostly desperate |

| GGUF | i1-IQ2_XXS | 9.6 | |

| GGUF | i1-IQ2_XS | 10.6 | |

| GGUF | i1-IQ2_S | 10.8 | |

| GGUF | i1-IQ2_M | 11.8 | |

| GGUF | i1-Q2_K_S | 12.3 | very low quality |

| GGUF | i1-Q2_K | 13.0 | IQ3_XXS probably better |

| GGUF | i1-IQ3_XXS | 13.7 | lower quality |

| GGUF | i1-Q3_K_S | 15.3 | IQ3_XS probably better |

| GGUF | i1-IQ3_M | 15.5 | |

| GGUF | i1-Q3_K_M | 16.9 | IQ3_S probably better |

| GGUF | i1-Q3_K_L | 18.2 | IQ3_M probably better |

| GGUF | i1-IQ4_XS | 18.8 | |

| GGUF | i1-Q4_0 | 19.9 | fast, low quality |

| GGUF | i1-Q4_K_S | 20.0 | optimal size/speed/quality |

| GGUF | i1-Q4_K_M | 21.3 | fast, recommended |

| GGUF | i1-Q5_K_S | 24.1 | |

| GGUF | i1-Q5_K_M | 24.8 | |

| GGUF | i1-Q6_K | 28.6 | practically like static Q6_K |

Here is a handy graph by ikawrakow comparing some lower-quality quant

types (lower is better):

!image.png

And here are Artefact2's thoughts on the matter:

https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to

questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting

me use its servers and providing upgrades to my workstation to enable

this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

<!-- end -->