← back to catalog · registered 2026-08-22 13:56

mradermacher/vicuna-7b-v1.5-uncensored-i1-GGUF

mradermacher 7B GGUF second-order 4K ctx
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Response includes
  • classification m8
  • files 24
  • hub_downloads_all_time 5,924
  • author_summary 3324 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='jdqqjr/vicuna-7b-v1.5-uncensored' (base has 'abliterated' marker, assume M1 default)
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
6K
461 last 30d - cooling
Likes
1
Model age
2.3y ago
created 2024-07-09
Downloads over time
Now6K→from1K↑494%
02.2K4.4K6.6K1K on Jul 24, 20246K on Oct 11Jul '24Nov '24Mar '25Jul '25Nov '25MarJul
Jul 24, 2024 → Oct 11 · 155 snapshots · spans 809 days

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Variants by this author 2 formats · 646 downloads combined

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

Metadata

Languages
en
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf en base_model:jdqqjr/vicuna-7b-v1.5-uncensored base_model:quantized:jdqqjr/vicuna-7b-v1.5-uncensored endpoints_compatible region:us imatrix conversational

Related

Total size
61.3 GB
Files
24
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2024-08-02 09:46

Files by quantization

Q6_K 1 file 5.15 GB
vicuna-7b-v1.5-uncensored.i1-Q6_K.gguf 5.15 GB 16eda1c5 download
Q5_K 2 files 8.79 GB
vicuna-7b-v1.5-uncensored.i1-Q5_K_M.gguf 4.45 GB 4bbd27d1 download
vicuna-7b-v1.5-uncensored.i1-Q5_K_S.gguf 4.33 GB d0858677 download
Q4_K 2 files 7.39 GB
vicuna-7b-v1.5-uncensored.i1-Q4_K_M.gguf 3.80 GB 3fc61c7d download
vicuna-7b-v1.5-uncensored.i1-Q4_K_S.gguf 3.59 GB dc5c6cad download
Q4 1 file 3.57 GB
vicuna-7b-v1.5-uncensored.i1-Q4_0.gguf 3.57 GB 91599fe5 download
IQ4 1 file 3.37 GB
vicuna-7b-v1.5-uncensored.i1-IQ4_XS.gguf 3.37 GB eeec617f download
Q3_K 3 files 9.17 GB
vicuna-7b-v1.5-uncensored.i1-Q3_K_L.gguf 3.35 GB 5beef68d download
vicuna-7b-v1.5-uncensored.i1-Q3_K_M.gguf 3.07 GB 92b868d4 download
vicuna-7b-v1.5-uncensored.i1-Q3_K_S.gguf 2.75 GB c735dc95 download
IQ3 4 files 10.7 GB
vicuna-7b-v1.5-uncensored.i1-IQ3_M.gguf 2.90 GB 4e334980 download
vicuna-7b-v1.5-uncensored.i1-IQ3_S.gguf 2.75 GB 7c6d7301 download
vicuna-7b-v1.5-uncensored.i1-IQ3_XS.gguf 2.60 GB 5ffb83f7 download
vicuna-7b-v1.5-uncensored.i1-IQ3_XXS.gguf 2.41 GB 54475593 download
Q2_K 1 file 2.36 GB
vicuna-7b-v1.5-uncensored.i1-Q2_K.gguf 2.36 GB c3a6ba11 download
IQ2 4 files 7.87 GB
vicuna-7b-v1.5-uncensored.i1-IQ2_M.gguf 2.20 GB 3f2b3176 download
vicuna-7b-v1.5-uncensored.i1-IQ2_S.gguf 2.05 GB b834e3aa download
vicuna-7b-v1.5-uncensored.i1-IQ2_XS.gguf 1.90 GB 5873fe68 download
vicuna-7b-v1.5-uncensored.i1-IQ2_XXS.gguf 1.73 GB ea77acc5 download
IQ1 2 files 2.96 GB
vicuna-7b-v1.5-uncensored.i1-IQ1_M.gguf 1.54 GB 17592b7c download
vicuna-7b-v1.5-uncensored.i1-IQ1_S.gguf 1.42 GB 9c1c2601 download
Auxiliary files 3 files 4.36 MB
imatrix.dat 4.35 MB a50e9fd8 download
README.md 5.17 KB be73b1bb download
.gitattributes 3.10 KB 663421fa download

README current version from Hugging Face


base_model: jdqqjr/vicuna-7b-v1.5-uncensored
language:

  • en
    library_name: transformers
    quantized_by: mradermacher

About

weighted/imatrix quants of https://huggingface.co/jdqqjr/vicuna-7b-v1.5-uncensored

static quants are available at https://huggingface.co/mradermacher/vicuna-7b-v1.5-uncensored-GGUF

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 i1-IQ1_S 1.6 for the desperate
GGUF i1-IQ1_M 1.8 mostly desperate
GGUF i1-IQ2_XXS 2.0
GGUF i1-IQ2_XS 2.1
GGUF i1-IQ2_S 2.3
GGUF i1-IQ2_M 2.5
GGUF i1-Q2_K 2.6 IQ3_XXS probably better
GGUF i1-IQ3_XXS 2.7 lower quality
GGUF i1-IQ3_XS 2.9
GGUF i1-IQ3_S 3.0 beats Q3_K*
GGUF i1-Q3_K_S 3.0 IQ3_XS probably better
GGUF i1-IQ3_M 3.2
GGUF i1-Q3_K_M 3.4 IQ3_S probably better
GGUF i1-Q3_K_L 3.7 IQ3_M probably better
GGUF i1-IQ4_XS 3.7
GGUF i1-Q4_0 3.9 fast, low quality
GGUF i1-Q4_K_S 4.0 optimal size/speed/quality
GGUF i1-Q4_K_M 4.2 fast, recommended
GGUF i1-Q5_K_S 4.8
GGUF i1-Q5_K_M 4.9
GGUF i1-Q6_K 5.6 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.

README history 3 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2024-08-02auto-patch README.md33b564e5.2 KB
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  2. 2024-07-09auto-patch README.mdbd1bcf85.1 KB
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  3. 2024-07-09uploaded from nethype/backc048b7b240 B
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