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Melvin56/GLM-4-9B-0414-abliterated-GGUF

Melvin56 Glm 9B GGUF second-order 33K ctx
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Response includes
  • classification m8
  • files 14
  • hub_downloads_all_time 4,476
  • author_summary 28 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
MEDIUM
Inherited from base model
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=1
  • assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
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
4K
988 last 30d - stable
Likes
0
Model age
17mo ago
created 2025-04-21
Downloads over time
Now4.6K→from61↑7,431%
01.7K3.4K5K61 on Apr 16, 20254.6K on Oct 11Apr '25Jul '25Oct '25JanAprJulOct
Apr 16, 2025 → Oct 11 · 117 snapshots · spans 543 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.

Metadata

License
mit
Languages
zh en
Quantizations
BF16 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf abliterated uncensored text-generation zh en license:mit endpoints_compatible region:us conversational

Related

Total size
75.9 GB
Files
14
Quantizations
8
Registered
2026-08-22 13:56
Last updated on HF
2025-04-26 10:06

Files by quantization

BF16 1 file 17.5 GB
glm-4-9b-0414-abliterated-BF16.gguf 17.5 GB 5f368bc9 download
Q8_0 1 file 9.31 GB
glm-4-9b-0414-abliterated-Q8_0.gguf 9.31 GB 32cc3813 download
Q6_K 1 file 7.70 GB
glm-4-9b-0414-abliterated-Q6_K.gguf 7.70 GB 12bd280f download
Q5_K 2 files 12.8 GB
glm-4-9b-0414-abliterated-Q5_K_M.gguf 6.57 GB 7c470d84 download
glm-4-9b-0414-abliterated-Q5_K_S.gguf 6.24 GB 72f1aca0 download
Q4_K 2 files 11.1 GB
glm-4-9b-0414-abliterated-Q4_K_M.gguf 5.74 GB dc224e81 download
glm-4-9b-0414-abliterated-Q4_K_S.gguf 5.36 GB c24883f4 download
Q3_K 3 files 13.7 GB
glm-4-9b-0414-abliterated-Q3_K_L.gguf 4.84 GB 97fb903a download
glm-4-9b-0414-abliterated-Q3_K_M.gguf 4.63 GB 9a2280a2 download
glm-4-9b-0414-abliterated-Q3_K_S.gguf 4.28 GB 40e95a3c download
Q2_K 1 file 3.73 GB
glm-4-9b-0414-abliterated-Q2_K.gguf 3.73 GB 33715daf download
Auxiliary files 3 files 5.23 MB
imatrix.dat 5.22 MB 305322a5 download
.gitattributes 2.38 KB ffca2acf download
README.md 1.39 KB 90e248f6 download

README current version from Hugging Face


license: mit
language:

  • zh
  • en
    pipeline_tag: text-generation
    base_model:
  • huihui-ai/GLM-4-9B-0414-abliterated
    library_name: transformers
    tags:
  • abliterated
  • uncensored

Melvin56/GLM-4-9B-0414-abliterated-GGUF

Original Model : huihui-ai/GLM-4-9B-0414-abliterated

Llama.cpp build: 558a7647 (5190)

I used imatrix to create all these quants using this Dataset.

Update-01
  * [Fixed Quant] Re-quantized all quants with build: 558a7647 (5190)
CPU (AVX2) CPU (ARM NEON) Metal cuBLAS rocBLAS SYCL CLBlast Vulkan Kompute
K-quants ✅ ✅ ✅ ✅ ✅ ✅ ✅ 🐢5 ✅ 🐢5 ❌
I-quants ✅ 🐢4 ✅ 🐢4 ✅ 🐢4 ✅ ✅ Partial¹ ❌ ❌ ❌
✅: feature works
🚫: feature does not work
❓: unknown, please contribute if you can test it youself
🐢: feature is slow
¹: IQ3_S and IQ1_S, see #5886
²: Only with -ngl 0
³: Inference is 50% slower
⁴: Slower than K-quants of comparable size
⁵: Slower than cuBLAS/rocBLAS on similar cards
⁶: Only q8_0 and iq4_nl

README history 3 versions

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

  1. 2025-04-26Update README.md9995d511.4 KB
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  2. 2025-04-22Update README.md8d4cc641.6 KB
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  3. 2025-04-22Upload folder using huggingface_hub74c3d434.9 KB
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