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Squish42/WizardLM-7B-Uncensored-GPTQ-8bit-128g

Squish42 Llama 7B
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Response includes
  • classification m-uncensored
  • files 9
  • hub_downloads_all_time 374
  • author_summary 2 models
  • readme_text full
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Abliteration classifier · v1.0.0
M-U
Primary method

Uncensored (method unknown)

No other method signals detected in this model.
Confidence
LOW
Why this label 3 signals
Weak or ambiguous signals. Best guess based on catalog patterns; treat as tentative and check the evidence below.
  • 'uncensored' in name/tags but no 'abliterated' marker
  • method not identifiable from author declaration alone
  • may be DPO fine-tune, prompt engineering, or unknown technique
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 · lifetime
374
21 last 30d - cooling
Likes
2
Model age
3.3y ago
created 2023-06-23
Downloads over time
Now382→from30↑1,173%
014028042030 on Jul 24, 2024382 on Oct 11Jul '24Nov '24Mar '25Jul '25Nov '25MarJul
Jul 24, 2024 → Oct 11 · 155 snapshots · spans 809 days

Metadata

License
unknown
Tags
transformers llama text-generation license:unknown endpoints_compatible region:us

Related

Total size
6.67 GB
Files
9
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2023-06-23 04:12

Files by quantization

Auxiliary files 9 files 6.67 GB
WizardLM-7B-Uncensored.safetensors 6.67 GB d958bc5b download
tokenizer.json 1.76 MB f57412e8 download
tokenizer.model 488 KB 9e556afd download
.gitattributes 1.48 KB 39e7ae7f download
README.md 959 B 2bf16439 download
quantize.py 957 B 4b581656 download
config.json 554 B a714e33e download
quantize_config.json 205 B b6238deb download
.gitignore 12.0 B 5dc0bd35 download

README current version from Hugging Face


license: unknown

ehartford/WizardLM-7B-Uncensored quantized to 8bit GPTQ with group size 128 + true sequential, no act order.

For most uses this probably isn't what you want.
For 4bit GPTQ quantizations see TheBloke/WizardLM-7B-uncensored-GPTQ

Quantized using AutoGPTQ with the following config:

config: dict = dict(
    quantize_config=dict(model_file_base_name='WizardLM-7B-Uncensored',
                         bits=8, desc_act=False, group_size=128, true_sequential=True),
    use_safetensors=True
)

See quantize.py for the full script.

Tested for compatibility with:

  • WSL with GPTQ-for-Llama triton branch.

AutoGPTQ loader should read configuration from quantize_config.json.
For GPTQ-for-Llama use the following configuration when loading:
wbits: 8
groupsize: 128
model_type: llama

README history 1 version

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

  1. 2023-06-23Initial commitbe6f120959 B
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