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mradermacher/Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base-i1-GGUF

mradermacher 800M GGUF second-order
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Response includes
  • classification m8
  • files 27
  • author_summary 3376 models
  • readme_text full
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Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
HIGH
Inherited from base model
Why this label 3 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • author=mradermacher (M8 quantization producer, never originator)
  • is_gguf=1
  • base_model='dalatexcoder/Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base' (base has 'abliterated' marker, assume M1 default)
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No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

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Downloads · 30-day
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Likes
0
Model age
today
created 2026-10-21

Genealogy 0 direct forks

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Variants by this author 2 formats · 0 downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

License
apache-2.0
Languages
en
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf heretic abliterated mlx en base_model:dalatexcoder/Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base base_model:quantized:dalatexcoder/Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base license:apache-2.0 endpoints_compatible region:us imatrix

Related

Total size
10.2 GB
Files
27
Quantizations
11
Registered
2026-10-21 10:00
Last updated on HF
2026-10-21 09:49

Files by quantization

Q6_K 1 file 601 MB
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-Q6_K.gguf 601 MB adaa3fcc download
Q5_K 2 files 1.06 GB
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-Q5_K_M.gguf 551 MB 155965d1 download
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-Q5_K_S.gguf 538 MB 7467ee43 download
Q4 2 files 987 MB
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-Q4_1.gguf 508 MB 29881e24 download
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-Q4_0.gguf 479 MB 2565a77e download
Q4_K 2 files 987 MB
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-Q4_K_M.gguf 505 MB c001d125 download
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-Q4_K_S.gguf 482 MB 3ee38980 download
IQ4 2 files 973 MB
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-IQ4_NL.gguf 492 MB 51152b7b download
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-IQ4_XS.gguf 481 MB 03d71324 download
Q3_K 3 files 1.30 GB
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-Q3_K_L.gguf 469 MB 130df627 download
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-Q3_K_M.gguf 445 MB 495ab182 download
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-Q3_K_S.gguf 415 MB 1228cfd1 download
IQ3 4 files 1.63 GB
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-IQ3_M.gguf 433 MB 9f77a4cc download
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-IQ3_S.gguf 430 MB bd638e42 download
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-IQ3_XS.gguf 423 MB 81801fd6 download
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-IQ3_XXS.gguf 380 MB 401a4c0e download
Q2_K 2 files 798 MB
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-Q2_K.gguf 403 MB b60af646 download
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-Q2_K_S.gguf 395 MB 8683ff30 download
IQ2 4 files 1.36 GB
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-IQ2_M.gguf 360 MB 07cc9227 download
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-IQ2_S.gguf 350 MB a20a490b download
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-IQ2_XS.gguf 347 MB 94e15615 download
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-IQ2_XXS.gguf 336 MB f5c91cd9 download
IQ1 2 files 637 MB
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-IQ1_M.gguf 323 MB defc7b4d download
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.i1-IQ1_S.gguf 315 MB efc6e20b download
Auxiliary files 3 files 2.18 MB
Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base.imatrix.gguf 2.17 MB ddad317b download
README.md 7.46 KB 45e9fb3c download
.gitattributes 3.76 KB 841a7373 download

README current version from Hugging Face


base_model: dalatexcoder/Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base
language:


About

weighted/imatrix quants of https://huggingface.co/dalatexcoder/Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base

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

static quants are available at https://huggingface.co/mradermacher/Rice-Cracker-Qwen3.5-0.8B-Abliterated-Base-GGUF

This is a vision model - mmproj files (if any) will be in the static repository.

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs
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 0.1 imatrix file (for creating your own quants)
GGUF i1-IQ1_S 0.4 for the desperate
GGUF i1-IQ1_M 0.4 mostly desperate
GGUF i1-IQ2_XXS 0.5
GGUF i1-IQ2_XS 0.5
GGUF i1-IQ2_S 0.5
GGUF i1-IQ2_M 0.5
GGUF i1-IQ3_XXS 0.5 lower quality
GGUF i1-Q2_K_S 0.5 very low quality
GGUF i1-Q2_K 0.5 IQ3_XXS probably better
GGUF i1-Q3_K_S 0.5 IQ3_XS probably better
GGUF i1-IQ3_XS 0.5
GGUF i1-IQ3_S 0.6 beats Q3_K*
GGUF i1-IQ3_M 0.6
GGUF i1-Q3_K_M 0.6 IQ3_S probably better
GGUF i1-Q3_K_L 0.6 IQ3_M probably better
GGUF i1-Q4_0 0.6 fast, low quality
GGUF i1-IQ4_XS 0.6
GGUF i1-Q4_K_S 0.6 optimal size/speed/quality
GGUF i1-IQ4_NL 0.6 prefer IQ4_XS
GGUF i1-Q4_K_M 0.6 fast, recommended
GGUF i1-Q4_1 0.6
GGUF i1-Q5_K_S 0.7
GGUF i1-Q5_K_M 0.7
GGUF i1-Q6_K 0.7 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.

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