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mradermacher/CodeLlama-34b-Instruct-hf-abliterated-GGUF

mradermacher Llama 34B GGUF second-order 16K ctx
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Response includes
  • classification m8
  • files 13
  • hub_downloads_all_time 1,749
  • 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 layer-wise ablation 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='huihui-ai/CodeLlama-34b-Instruct-hf-abliterated' (base is huihui-ai model (M3))
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Downloads · lifetime
2K
117 last 30d - cooling
Likes
0
Model age
20mo ago
created 2025-02-11
Downloads over time
Now1.8K→from211↑750%
1327391.3K2K211 on Feb 12, 20251.8K on Oct 11Feb '25May '25Aug '25Nov '25FebMayAug
Feb 12, 2025 → Oct 11 · 126 snapshots · spans 606 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 · 374 downloads combined

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

Metadata

License
llama2
Languages
code
Quantizations
IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf facebook meta pytorch llama llama-2 abliterated uncensored code license:llama2 endpoints_compatible

Related

Total size
214 GB
Files
13
Quantizations
8
Registered
2026-08-22 13:56
Last updated on HF
2025-02-12 23:21

Files by quantization

Q8_0 1 file 33.4 GB
CodeLlama-34b-Instruct-hf-abliterated.Q8_0.gguf 33.4 GB 06ef0136 download
Q6_K 1 file 25.8 GB
CodeLlama-34b-Instruct-hf-abliterated.Q6_K.gguf 25.8 GB 961b027b download
Q5_K 2 files 43.8 GB
CodeLlama-34b-Instruct-hf-abliterated.Q5_K_M.gguf 22.2 GB 12ec4244 download
CodeLlama-34b-Instruct-hf-abliterated.Q5_K_S.gguf 21.6 GB 310f0c17 download
Q4_K 2 files 36.7 GB
CodeLlama-34b-Instruct-hf-abliterated.Q4_K_M.gguf 18.8 GB 89c685a9 download
CodeLlama-34b-Instruct-hf-abliterated.Q4_K_S.gguf 17.9 GB 77a05528 download
IQ4 1 file 17.0 GB
CodeLlama-34b-Instruct-hf-abliterated.IQ4_XS.gguf 17.0 GB a34081e3 download
Q3_K 3 files 45.3 GB
CodeLlama-34b-Instruct-hf-abliterated.Q3_K_L.gguf 16.6 GB 0b5504f5 download
CodeLlama-34b-Instruct-hf-abliterated.Q3_K_M.gguf 15.2 GB 59053c00 download
CodeLlama-34b-Instruct-hf-abliterated.Q3_K_S.gguf 13.6 GB 593d57b9 download
Q2_K 1 file 11.6 GB
CodeLlama-34b-Instruct-hf-abliterated.Q2_K.gguf 11.6 GB 26f0f460 download
Auxiliary files 2 files 18.1 KB
README.md 15.7 KB a49046d8 download
.gitattributes 2.40 KB a0d0a7a1 download

README current version from Hugging Face


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  • code
    library_name: transformers
    license: llama2
    quantized_by: mradermacher
    tags:
  • facebook
  • meta
  • pytorch
  • llama
  • llama-2
  • abliterated
  • uncensored

About

static quants of https://huggingface.co/huihui-ai/CodeLlama-34b-Instruct-hf-abliterated

weighted/imatrix quants are available at https://huggingface.co/mradermacher/CodeLlama-34b-Instruct-hf-abliterated-i1-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 Q2_K 12.6
GGUF Q3_K_S 14.7
GGUF Q3_K_M 16.4 lower quality
GGUF Q3_K_L 17.9
GGUF IQ4_XS 18.3
GGUF Q4_K_S 19.3 fast, recommended
GGUF Q4_K_M 20.3 fast, recommended
GGUF Q5_K_S 23.3
GGUF Q5_K_M 23.9
GGUF Q6_K 27.8 very good quality
GGUF Q8_0 36.0 fast, best quality

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.

README history 4 versions

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

  1. 2025-02-12auto-patch README.mdcb581aa15.7 KB
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  2. 2025-02-12auto-patch README.md97b944c15.8 KB
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  3. 2025-02-11auto-patch README.mdff99f3715.5 KB
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  4. 2025-02-11uploaded from rich1585188b237 B
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