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tpls/gemma-4-12B-coder-fable5-composer2.5-v1-abliterated-sft-v5-GGUF

tpls Gemma 12B GGUF second-order 262K ctx
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Response includes
  • classification m8
  • files 3
  • hub_downloads_all_time 371
  • author_summary 6 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
371
51 last 30d - stable
Likes
0
Model age
3mo ago
created 2026-06-25
Downloads over time
Now383→from150↑155%
138228317406150 on Jun 24383 on Oct 12383 on Oct 9JunJulAugSepOct
Jun 24 → Oct 12 · 56 snapshots · spans 110 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 · 55 downloads combined

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

Metadata

License
gemma
Quantizations
Q4_K
Tags
gguf llama.cpp gemma4 abliterated code text-generation base_model:tpls/gemma-4-12B-coder-fable5-composer2.5-v1-abliterated-sft-v5 base_model:quantized:tpls/gemma-4-12B-coder-fable5-composer2.5-v1-abliterated-sft-v5 license:gemma endpoints_compatible region:us imatrix

Related

Total size
7.98 GB
Files
3
Quantizations
2
Registered
2026-08-22 13:56
Last updated on HF
2026-06-25 15:36

Files by quantization

Q4_K 1 file 7.98 GB
gemma-4-12B-coder-fable5-composer2.5-v1-abliterated-sft-Q4_K_M.gguf 7.98 GB 406fe5fe download
Auxiliary files 2 files 3.97 KB
README.md 2.39 KB d9d29f1c download
.gitattributes 1.58 KB e4c0aa50 download

README current version from Hugging Face


base_model: tpls/gemma-4-12B-coder-fable5-composer2.5-v1-abliterated-sft-v5
base_model_relation: quantized
library_name: gguf
pipeline_tag: text-generation
license: gemma
quantized_by: triplezrobotics
tags:

  • gguf
  • llama.cpp
  • gemma4
  • abliterated
  • code

gemma-4-12B-coder-fable5-composer2.5-v1-abliterated-sft-v5-GGUF

GGUF quantizations of tpls/gemma-4-12B-coder-fable5-composer2.5-v1-abliterated-sft-v5.

Quantized with llama.cpp using an importance matrix (imatrix) calibrated on
code + tool-call markup, with token-embedding and output tensors kept at f16
to protect the tool-call token logits, plus a gemma-4 EOG patch (eot=106) to
bound the <|turn> runaway.

Files

Quant File Notes
Q4_K_M gemma-4-12B-coder-fable5-composer2.5-v1-abliterated-sft-Q4_K_M.gguf good default — fits 12 GB VRAM, best size/quality balance

Use it

# llama.cpp (server, with native tool parsing)
llama-server -hf tpls/gemma-4-12B-coder-fable5-composer2.5-v1-abliterated-sft-v5-GGUF:Q4_K_M --jinja --ctx-size 16384

# Ollama
ollama run hf.co/tpls/gemma-4-12B-coder-fable5-composer2.5-v1-abliterated-sft-v5-GGUF:Q4_K_M

⚠️ Tool-calling note (abliterated weights)

The base model and fine-tune emit canonical tool_calls that llama.cpp --jinja
parses natively. Abliteration degrades the canonical tool token: this model
tends to leak its calls as text markup (<|tool>NAME{...}) instead of the
canonical <|tool_call> token, so the native parser may not fire.

Two ways to get structured tool_calls back:

  1. Runtime shim (works now). Put a tolerant recovery shim in front via LiteLLM:

    # litellm config
    model_list:
      - model_name: gemma-coder
        litellm_params:
          model: openai/gemma-coder
          api_base: http://127.0.0.1:8096/v1
          api_key: sk-none
    litellm_settings:
      callbacks: ["gemma_tool_shim.shim"]   # recovers tool_calls from leaked markup
      drop_params: true
    

    The shim is published with the source at the repo that produced this model.

  2. Native (no shim). Use a control-vector / activation-steered variant
    instead of weight-ablation — steering uncensors at inference without editing
    the weights, so the canonical tool token survives and bare --jinja works.

README history 1 version

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

  1. 2026-06-25model card34e72742.4 KB
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