← back to catalog · registered 2026-09-18 18:56

mangomikemike/Swift-Qwen3.8-27B-Uncensored-GPTQ-Int4-sym-G128-MTP-BF16-Q4_K_M-GGUF

mangomikemike 27B GGUF multimodal second-order
curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/mangomikemike%2FSwift-Qwen3.8-27B-Uncensored-GPTQ-Int4-sym-G128-MTP-BF16-Q4_K_M-GGUF"
Response includes
  • classification m8
  • files 3
  • author_summary 1 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 · 30-day
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Model age
today
created 2026-09-18

Genealogy 0 direct forks

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Metadata

License
other
Languages
en zh
Tags
transformers gguf gptq int4 uncensored abliterated mtp speculative-decoding intel arc intel-arc xpu

Related

Total size
15.7 GB
Files
3
Quantizations
1
Registered
2026-09-18 18:56
Last updated on HF
2026-09-18 18:38

Files by quantization

Auxiliary files 3 files 15.7 GB
swift-qwen3.8-27b-uncensored-gptq-int4-sym-g128-mtp-bf16-q4_k_m.gguf 15.7 GB b0c6e7f1 download
README.md 2.55 KB 9921381a download
.gitattributes 1.59 KB 256958c8 download

README current version from Hugging Face


license: other
license_name: swift-open-license-1.0
license_link: https://ukisai.com/contact
base_model: greglechin/Swift-Qwen3.8-27B-Uncensored-GPTQ-Int4-sym-G128-MTP-BF16
base_model_relation: quantized
library_name: transformers
language:

  • en
  • zh
    pipeline_tag: image-text-to-text
    tags:
  • gptq
  • int4
  • uncensored
  • abliterated
  • mtp
  • speculative-decoding
  • intel
  • arc
  • intel-arc
  • xpu
  • vllm
  • qwen3.8
  • swift
  • llama-cpp
  • gguf-my-repo

mangomikemike/Swift-Qwen3.8-27B-Uncensored-GPTQ-Int4-sym-G128-MTP-BF16-Q4_K_M-GGUF

This model was converted to GGUF format from greglechin/Swift-Qwen3.8-27B-Uncensored-GPTQ-Int4-sym-G128-MTP-BF16 using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo mangomikemike/Swift-Qwen3.8-27B-Uncensored-GPTQ-Int4-sym-G128-MTP-BF16-Q4_K_M-GGUF --hf-file swift-qwen3.8-27b-uncensored-gptq-int4-sym-g128-mtp-bf16-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo mangomikemike/Swift-Qwen3.8-27B-Uncensored-GPTQ-Int4-sym-G128-MTP-BF16-Q4_K_M-GGUF --hf-file swift-qwen3.8-27b-uncensored-gptq-int4-sym-g128-mtp-bf16-q4_k_m.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo mangomikemike/Swift-Qwen3.8-27B-Uncensored-GPTQ-Int4-sym-G128-MTP-BF16-Q4_K_M-GGUF --hf-file swift-qwen3.8-27b-uncensored-gptq-int4-sym-g128-mtp-bf16-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo mangomikemike/Swift-Qwen3.8-27B-Uncensored-GPTQ-Int4-sym-G128-MTP-BF16-Q4_K_M-GGUF --hf-file swift-qwen3.8-27b-uncensored-gptq-int4-sym-g128-mtp-bf16-q4_k_m.gguf -c 2048
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