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mradermacher/llama7b-wizardlm-unfiltered-i1-GGUF

mradermacher Llama GGUF second-order
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Response includes
  • classification m8
  • files 24
  • author_summary 3324 models
  • readme_text full
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Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

No other method signals detected in this model.
Confidence
HIGH
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)
  • is_gguf=1
  • base_model='ausboss/llama7b-wizardlm-unfiltered' (source unknown method)
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.

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Downloads · 30-day
718
↑ 831% in 90 days
Likes
0
Model age
2.1y ago
created 2024-09-14
Downloads over time
Now6.8K→from728↑831%
02.5K5K7.4K728 on Sep 11, 20246.8K on Oct 11Sep '24Jan '25May '25Sep '25JanMaySep
Sep 11, 2024 → Oct 11 · 148 snapshots · spans 760 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 · 970 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:ausboss/llama7b-wizardlm-unfiltered base_model:quantized:ausboss/llama7b-wizardlm-unfiltered endpoints_compatible region:us imatrix

Related

Total size
61.3 GB
Files
24
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2024-09-14 10:15

Files by quantization

Q6_K 1 file 5.15 GB
llama7b-wizardlm-unfiltered.i1-Q6_K.gguf 5.15 GB 315760a9 download
Q5_K 2 files 8.79 GB
llama7b-wizardlm-unfiltered.i1-Q5_K_M.gguf 4.45 GB a544b102 download
llama7b-wizardlm-unfiltered.i1-Q5_K_S.gguf 4.33 GB 790e3f02 download
Q4_K 2 files 7.39 GB
llama7b-wizardlm-unfiltered.i1-Q4_K_M.gguf 3.80 GB 0e69ac2a download
llama7b-wizardlm-unfiltered.i1-Q4_K_S.gguf 3.59 GB 5988b661 download
Q4 1 file 3.57 GB
llama7b-wizardlm-unfiltered.i1-Q4_0.gguf 3.57 GB 66349416 download
IQ4 1 file 3.37 GB
llama7b-wizardlm-unfiltered.i1-IQ4_XS.gguf 3.37 GB c3ed1150 download
Q3_K 3 files 9.17 GB
llama7b-wizardlm-unfiltered.i1-Q3_K_L.gguf 3.35 GB c979561c download
llama7b-wizardlm-unfiltered.i1-Q3_K_M.gguf 3.07 GB e8c71230 download
llama7b-wizardlm-unfiltered.i1-Q3_K_S.gguf 2.75 GB 4d542d48 download
IQ3 4 files 10.7 GB
llama7b-wizardlm-unfiltered.i1-IQ3_M.gguf 2.90 GB 50c7baa8 download
llama7b-wizardlm-unfiltered.i1-IQ3_S.gguf 2.75 GB 5a161072 download
llama7b-wizardlm-unfiltered.i1-IQ3_XS.gguf 2.60 GB 3179133d download
llama7b-wizardlm-unfiltered.i1-IQ3_XXS.gguf 2.41 GB 0f41efac download
Q2_K 1 file 2.36 GB
llama7b-wizardlm-unfiltered.i1-Q2_K.gguf 2.36 GB 2d45734b download
IQ2 4 files 7.87 GB
llama7b-wizardlm-unfiltered.i1-IQ2_M.gguf 2.20 GB fe63833a download
llama7b-wizardlm-unfiltered.i1-IQ2_S.gguf 2.05 GB c6eaa282 download
llama7b-wizardlm-unfiltered.i1-IQ2_XS.gguf 1.90 GB 76207bfd download
llama7b-wizardlm-unfiltered.i1-IQ2_XXS.gguf 1.73 GB a47fffc3 download
IQ1 2 files 2.96 GB
llama7b-wizardlm-unfiltered.i1-IQ1_M.gguf 1.54 GB 115ce95f download
llama7b-wizardlm-unfiltered.i1-IQ1_S.gguf 1.42 GB 4eef3cbc download
Auxiliary files 3 files 4.36 MB
imatrix.dat 4.35 MB d05a9f9d download
README.md 5.26 KB 6d9bd642 download
.gitattributes 3.14 KB effaa075 download

README current version from Hugging Face


base_model: ausboss/llama7b-wizardlm-unfiltered
language:

  • en
    library_name: transformers
    quantized_by: mradermacher

About

weighted/imatrix quants of https://huggingface.co/ausboss/llama7b-wizardlm-unfiltered

static quants are available at https://huggingface.co/mradermacher/llama7b-wizardlm-unfiltered-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 2 versions

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

  1. 2024-09-14auto-patch README.md915d9ee5.3 KB
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  2. 2024-09-14uploaded from nethype/rain44770fb243 B
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