Transformers
GGUF
MLX
English
Chinese
unsloth
fine tune
heretic
abliterated
uncensored
creative
creative writing
fiction writing
plot generation
sub-plot generation
story generation
scene continue
storytelling
fiction story
science fiction
romance
all genres
story
writing
vivid prosing
vivid writing
fiction
roleplaying
bfloat16
all use cases
Deckard(qx)
mxfp8
mxfp4
Merge
mergekit
conversational
File size: 4,349 Bytes
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base_model: nightmedia/Qwen3.5-4B-Element
language:
- en
- zh
library_name: transformers
license: apache-2.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- unsloth
- fine tune
- heretic
- abliterated
- uncensored
- creative
- creative writing
- fiction writing
- plot generation
- sub-plot generation
- fiction writing
- story generation
- scene continue
- storytelling
- fiction story
- science fiction
- romance
- all genres
- story
- writing
- vivid prosing
- vivid writing
- fiction
- roleplaying
- bfloat16
- all use cases
- Deckard(qx)
- mxfp8
- mxfp4
- merge
- mergekit
- mlx
---
## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static quants of https://huggingface.co/nightmedia/Qwen3.5-4B-Element
<!-- provided-files -->
***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Qwen3.5-4B-Element-GGUF).***
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen3.5-4B-Element-i1-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](https://huggingface.co/mradermacher/Qwen3.5-4B-Element-GGUF/resolve/main/Qwen3.5-4B-Element.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.5 | multi-modal supplement |
| [GGUF](https://huggingface.co/mradermacher/Qwen3.5-4B-Element-GGUF/resolve/main/Qwen3.5-4B-Element.mmproj-f16.gguf) | mmproj-f16 | 0.8 | multi-modal supplement |
| [GGUF](https://huggingface.co/mradermacher/Qwen3.5-4B-Element-GGUF/resolve/main/Qwen3.5-4B-Element.Q2_K.gguf) | Q2_K | 2.0 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen3.5-4B-Element-GGUF/resolve/main/Qwen3.5-4B-Element.Q3_K_S.gguf) | Q3_K_S | 2.2 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen3.5-4B-Element-GGUF/resolve/main/Qwen3.5-4B-Element.Q3_K_M.gguf) | Q3_K_M | 2.4 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen3.5-4B-Element-GGUF/resolve/main/Qwen3.5-4B-Element.Q3_K_L.gguf) | Q3_K_L | 2.5 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen3.5-4B-Element-GGUF/resolve/main/Qwen3.5-4B-Element.IQ4_XS.gguf) | IQ4_XS | 2.6 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen3.5-4B-Element-GGUF/resolve/main/Qwen3.5-4B-Element.Q4_K_S.gguf) | Q4_K_S | 2.7 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Qwen3.5-4B-Element-GGUF/resolve/main/Qwen3.5-4B-Element.Q4_K_M.gguf) | Q4_K_M | 2.8 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Qwen3.5-4B-Element-GGUF/resolve/main/Qwen3.5-4B-Element.Q5_K_S.gguf) | Q5_K_S | 3.1 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen3.5-4B-Element-GGUF/resolve/main/Qwen3.5-4B-Element.Q5_K_M.gguf) | Q5_K_M | 3.2 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen3.5-4B-Element-GGUF/resolve/main/Qwen3.5-4B-Element.Q6_K.gguf) | Q6_K | 3.6 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen3.5-4B-Element-GGUF/resolve/main/Qwen3.5-4B-Element.Q8_0.gguf) | Q8_0 | 4.6 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen3.5-4B-Element-GGUF/resolve/main/Qwen3.5-4B-Element.f16.gguf) | f16 | 8.5 | 16 bpw, overkill |
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

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](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.
<!-- end -->
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