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Recouper/Mistral-7B-Instruct-v0.3-abliterated-Q5_K_M-GGUF

Recouper Mistral 7B GGUF second-order 33K ctx
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  • classification m8
  • files 3
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  • author_summary 8 models
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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
504
92 last 30d - stable
Likes
0
Model age
2mo ago
created 2026-07-26
Downloads over time
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Jul 29 → Oct 11 · 51 snapshots · spans 74 days

Genealogy 0 direct forks

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Metadata

Tags
gguf llama-cpp gguf-my-repo base_model:richardyoung/Mistral-7B-Instruct-v0.3-abliterated base_model:quantized:richardyoung/Mistral-7B-Instruct-v0.3-abliterated endpoints_compatible region:us

Related

Total size
4.78 GB
Files
3
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-07-26 08:54

Files by quantization

Auxiliary files 3 files 4.78 GB
mistral-7b-instruct-v0.3-abliterated-q5_k_m.gguf 4.78 GB 7f381bcb download
README.md 1.96 KB b50e1a18 download
.gitattributes 1.57 KB 5af5157c download

README current version from Hugging Face


base_model: richardyoung/Mistral-7B-Instruct-v0.3-abliterated
tags:

  • llama-cpp
  • gguf-my-repo

Recouper/Mistral-7B-Instruct-v0.3-abliterated-Q5_K_M-GGUF

This model was converted to GGUF format from richardyoung/Mistral-7B-Instruct-v0.3-abliterated 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 Recouper/Mistral-7B-Instruct-v0.3-abliterated-Q5_K_M-GGUF --hf-file mistral-7b-instruct-v0.3-abliterated-q5_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Recouper/Mistral-7B-Instruct-v0.3-abliterated-Q5_K_M-GGUF --hf-file mistral-7b-instruct-v0.3-abliterated-q5_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 Recouper/Mistral-7B-Instruct-v0.3-abliterated-Q5_K_M-GGUF --hf-file mistral-7b-instruct-v0.3-abliterated-q5_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Recouper/Mistral-7B-Instruct-v0.3-abliterated-Q5_K_M-GGUF --hf-file mistral-7b-instruct-v0.3-abliterated-q5_k_m.gguf -c 2048

README history 1 version

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

  1. 2026-07-26Upload README.md with huggingface_huba6a154e2 KB
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