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Hikari07jp/Maple-Preview-TQ2-Abliterated
Maple-Preview-TQ2-Abliterated is a text generation model from Hikari07jp. Use it when you need the model to write or continue text. It is set up for llama.cpp. The card lists the license as apache-2.0.
Quant-native abliterated build of deepgrove/maple-preview-GGUF (maple-preview-TQ20-head-Q4K).
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.gguf5.9 GB · 100%
From the Hugging Face model README
Quant-native abliterated build of deepgrove/maple-preview-GGUF (maple-preview-TQ2_0-head-Q4_K).
This is a research weight. It weakens refusals and keeps coding near the parent on a locked pilot. It is not a polished chat model.
| File | Role |
|---|---|
Maple-Preview-TQ2-Abliterated.gguf | language model (~5.9 GB) |
SHA256:
fde3633e525195bd1553c1cb6a4670d1cde20d294f8aa926a680da994652571a
# Needs a maple-capable llama.cpp build
./llama-server \
-m Maple-Preview-TQ2-Abliterated.gguf \
--host 127.0.0.1 --port 8080 \
-c 4096 -ngl 99 -np 1 --seed 0
{
"temperature": 0,
"seed": 0,
"top_k": 1,
"top_p": 1.0,
"min_p": 0.0,
"repeat_penalty": 1.0,
"chat_template_kwargs": {"enable_thinking": false}
}
temperature=0 alone is not enough on this MoE stack; pin seed and top_k=1.
ffn_down_exps tensors only:
empty==0.Full public method/recipe: hikarioyama/maple-tq2-quant-native-abliteration. This HF repo is the weight only.
Changed footprint vs parent (byte-level):
These are not a full leaderboard reproduction. All under the decode lock above, Maple llama-server, executable coding grader, paired harmful metrics.
| model | pass/60 | notes |
|---|---|---|
| parent TQ2 | 36 | baseline |
| ablit seed only | 26 | refusal removed, capability drop |
| this weight | 36 | parent score parity |
Reproducibility: n=3 reruns on this file gave 36/36/36 with text-identical generations under the lock (GPU0/1).
Score parity ≠ identical failures. On the n=60 pair table, parent-only pass and product-only pass were both 11 items.
| value | |
|---|---|
| parent baseline refusal-like slots | 36/36 counted hard-convert denominator |
| hard convert (HC) | 34/36 |
| empty completions | 0 |
Interpretation: refusals are largely weakened vs parent. This is an abliterated model.
Direct chat is not clean.
On a fixed 12-prompt collapse bench (identity / Japanese smalltalk / strict formatting / JSON-only / short controls):
| model | collapse/12 |
|---|---|
| parent chat baseline | 7/12 |
| this weight | 5/12 |
So collapse rate is a bit better than parent on that bench, but still present and ugly.
Typical failure mode:
We need to answer the user's question: "Who are you you you you you you..."
or Japanese punctuation loops (、、、、...), or planner monologue instead of the final answer.
Also observed:
frequency_penalty, DRY) can reduce loops but hurt refusal/coding gates in our tests — not enabled in the recommended lockDo not market this as a stable general chat model.
This model is more willing to answer requests the parent refuses. Use only in contexts where that is intended and lawful. No safety filter is baked in at serve time.
L18 full + L20 p25 s0 + L23 full + L17 p28 s7 on chat seed)