| --- |
| license: gemma |
| base_model: |
| - google/gemma-4-12B |
| library_name: transformers |
| pipeline_tag: text-generation |
| tags: |
| - gemma4 |
| - sft |
| - finetune |
| - reasoning |
| - roleplay |
| - tool-use |
| --- |
| <!doctype html> |
| <html lang="en"> |
| <head> |
| <meta charset="UTF-8" /> |
| <meta name="viewport" content="width=device-width, initial-scale=1.0" /> |
| <title>SpoomplesMaxx Whiskeyjack 12B</title> |
| </head> |
| <style> |
| @import url("https://fonts.googleapis.com/css2?family=Consolas&display=swap"); |
| .crt-container { |
| padding: 10px; |
| max-width: 1000px; |
| margin: 0 auto; |
| width: 95%; |
| } |
| .crt-case { |
| background: #e8d7c3; |
| border-radius: 10px; |
| padding: 15px; |
| box-shadow: |
| inset -2px -2px 5px rgba(0, 0, 0, 0.3), |
| 2px 2px 5px rgba(0, 0, 0, 0.2); |
| } |
| .crt-inner-case { |
| background: #e8d7c3; |
| border-radius: 8px; |
| padding: 3px; |
| box-shadow: |
| inset -1px -1px 4px rgba(0, 0, 0, 0.3), |
| 1px 1px 4px rgba(0, 0, 0, 0.2); |
| } |
| .crt-bezel { |
| background: linear-gradient(145deg, #1a1a1a, #2a2a2a); |
| padding: 15px; |
| border-radius: 5px; |
| border: 3px solid #0a0a0a; |
| position: relative; |
| box-shadow: |
| inset 0 0 20px rgba(0, 0, 0, 0.5), |
| inset 0 0 4px rgba(0, 0, 0, 0.4), |
| inset 2px 2px 4px rgba(255, 255, 255, 0.05), |
| inset -2px -2px 4px rgba(0, 0, 0, 0.8), |
| 0 0 2px rgba(0, 0, 0, 0.6), |
| -1px -1px 4px rgba(255, 255, 255, 0.1), |
| 1px 1px 4px rgba(0, 0, 0, 0.3); |
| } |
| .crt-bezel::before { |
| content: ""; |
| position: absolute; |
| top: 0; |
| left: 0; |
| right: 0; |
| bottom: 0; |
| background: linear-gradient( |
| 45deg, |
| rgba(255, 255, 255, 0.03) 0%, |
| rgba(255, 255, 255, 0) 40%, |
| rgba(0, 0, 0, 0.1) 60%, |
| rgba(0, 0, 0, 0.2) 100% |
| ); |
| border-radius: 3px; |
| pointer-events: none; |
| } |
| .terminal-screen { |
| background: #0c100d; |
| padding: 20px; |
| border-radius: 15px; |
| position: relative; |
| overflow: hidden; |
| font-family: "Consolas", monospace; |
| font-size: clamp(12px, 1.5vw, 16px); |
| color: #3dc862; |
| line-height: 1.4; |
| text-shadow: 0 0 2px #3dc862; |
| filter: brightness(1.1) contrast(1.1); |
| box-shadow: |
| inset 0 0 30px rgba(0, 0, 0, 0.9), |
| inset 0 0 8px rgba(0, 0, 0, 0.8), |
| 0 0 5px rgba(0, 0, 0, 0.6); |
| max-width: 80ch; |
| margin: 0 auto; |
| } |
| .terminal-screen h2, |
| .terminal-screen h3 { |
| font-size: clamp(16px, 2vw, 20px); |
| margin-bottom: 1em; |
| color: #ffdf00; |
| text-shadow: 0 0 3px rgba(255, 223, 0, 0.5); |
| } |
| .terminal-screen pre.code-block-image { |
| display: inline-block; |
| text-align: left; |
| font-size: clamp(2px, 0.4vw, 12px); |
| font-family: monospace; |
| margin: 1em 0; |
| background-color: #1a1a1a; |
| padding: 1em; |
| border-radius: 4px; |
| color: #3dc862; |
| overflow-x: auto; |
| line-height: 1; |
| max-width: 100%; |
| overflow: hidden; |
| white-space: pre; |
| } |
| .terminal-screen pre.code-block { |
| display: inline-block; |
| text-align: left; |
| font-size: clamp(10px, 1.3vw, 14px); |
| font-family: monospace; |
| margin: 1em 0; |
| background-color: #1a1a1a; |
| padding: 1em; |
| border-radius: 4px; |
| color: #3dc862; |
| overflow-x: auto; |
| line-height: 1; |
| max-width: 100%; |
| overflow: hidden; |
| white-space: pre; |
| } |
| .terminal-screen::before { |
| content: ""; |
| position: absolute; |
| top: 0; |
| left: 0; |
| right: 0; |
| bottom: 0; |
| background: |
| linear-gradient( |
| rgba(18, 16, 16, 0) 50%, |
| rgba(0, 0, 0, 0.25) 50% |
| ), |
| url("data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADIAAAAyBAMAAADsEZWCAAAAGFBMVEUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA4o8JoAAAAB3RSTlMAGwQIEQMYADcPzwAAACJJREFUKM9jYBgFo2AU0Beg+A8YMCLxGYZCbNQEo4BaAAD5TQiR5wU9vAAAAABJRU5ErkJggg=="); |
| background-size: 100% 2.5px; |
| pointer-events: none; |
| z-index: 2; |
| } |
| .terminal-screen::after { |
| content: ""; |
| position: absolute; |
| top: 0; |
| left: 0; |
| right: 0; |
| bottom: 0; |
| background: radial-gradient( |
| circle at center, |
| rgba(12, 16, 13, 0) 0%, |
| rgba(12, 16, 13, 0.2) 50%, |
| rgba(12, 16, 13, 0.15) 100% |
| ); |
| border-radius: 20px; |
| pointer-events: none; |
| z-index: 1; |
| } |
| .terminal-screen .notice { |
| margin: 1.5em 0; |
| padding: 0.8em 1.2em; |
| border: 1px solid #ffdf00; |
| border-radius: 4px; |
| background-color: rgba(255, 223, 0, 0.04); |
| } |
| .terminal-screen .notice h3 { |
| margin-top: 0.2em; |
| margin-bottom: 0.5em; |
| } |
| .terminal-screen .notice p { |
| margin-bottom: 0.2em; |
| } |
| .terminal-screen strong, |
| .terminal-screen em { |
| color: #f0f0f0; |
| } |
| .terminal-screen p, |
| .terminal-screen li { |
| color: #3dc862; |
| } |
| .terminal-screen a { |
| color: #5da9ff; |
| text-decoration: underline; |
| text-shadow: 0 0 2px rgba(93, 169, 255, 0.5); |
| transition: opacity 0.2s; |
| } |
| .terminal-screen a:hover { |
| opacity: 0.8; |
| } |
| .terminal-screen code, |
| .terminal-screen kbd, |
| .terminal-screen samp { |
| color: #3dc862; |
| font-family: "Consolas", monospace; |
| text-shadow: 0 0 2px #3dc862; |
| background-color: #1a1a1a; |
| padding: 0.2em 0.4em; |
| border-radius: 4px; |
| } |
| </style> |
| <div class="crt-container"> |
| <div class="crt-case"> |
| <div class="crt-inner-case"> |
| <div class="crt-bezel"> |
| <div class="terminal-screen"> |
| <div style="text-align: center"> |
| <h2>SpoomplesMaxx-Whiskeyjack-12B</h2> |
| <h3>"Camp Robber"</h3> |
| <pre class="code-block-image"> |
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| </pre> |
| </div> |
| <p> |
| SpoomplesMaxx is a generalist model line with |
| primary strengths in creative writing and roleplay, |
| plus competence at instruction following, |
| reasoning, and tool calling. Whiskeyjack brings the |
| corvid line to Gemma: a full-parameter SFT of |
| <strong>gemma-4-12B</strong>, trained in both |
| thinking and non-thinking modes, with thinking off |
| by default. |
| </p> |
| <p> |
| Named for <em>Perisoreus canadensis</em> — the |
| Canada jay, better known as the whisky jack or camp |
| robber. A corvid bold enough to land on your hand |
| and fly off with your lunch. The 35B got the |
| jackdaw; the 12B gets the smaller, friendlier |
| thief. |
| </p> |
| <h3>Prompt format</h3> |
| <p> |
| Gemma 4 uses a new turn format. It shares nothing |
| with Gemma 3 — there is no |
| <code><start_of_turn></code> — and the |
| assistant role is spelled <code>model</code>: |
| </p> |
| <pre class="code-block"> |
| <|turn>user |
| ...<turn|> |
| <|turn>model |
| <|channel>thought |
| ...reasoning... |
| <channel|>...answer...<turn|> |
| </pre> |
| <pre class="code-block"> |
| STOPS: stop on <turn|> (id 106). <eos> (id 1) is kept as a secondary |
| EOS, but never set <eos> alone -- turns end on <turn|>. |
| </pre> |
| <p> |
| The control tokens (<code><turn|></code>, |
| <code><|channel></code>/<code><channel|></code>, |
| <code><|tool_call></code>/<code><tool_call|></code>) |
| were audited before training and re-verified after |
| it: stop battery, boundary probes, and a tool-call |
| battery all pass on the published checkpoint. |
| </p> |
| <h3>Thinking behavior</h3> |
| <p> |
| Thinking is opt-in and <strong>off by |
| default</strong>. A <code><|think|></code> |
| marker at the top of the <strong>system</strong> |
| turn switches it on; |
| <code>apply_chat_template(enable_thinking=True)</code> |
| injects it for you. Both modes share the same bare |
| <code><|turn>model</code> generation prefix — |
| the model decides on its own whether to open |
| <code><|channel>thought</code>. |
| </p> |
| <pre class="code-block"> |
| MODE CONTROL: |
| (default) thinking OFF -- no marker, no thought channel |
| enable_thinking=True injects <|think|> into the system turn; the |
| model opens <|channel>thought on its own |
| |
| PARSER NOTE: reasoning sits between <|channel>thought and <channel|>; |
| the visible answer follows <channel|> in the same turn |
| </pre> |
| <div class="notice"> |
| <h3>The chat template is not stock Gemma 4</h3> |
| <p> |
| Upstream Gemma 4 appends an empty thought |
| channel |
| (<code><|channel>thought\n<channel|></code>) |
| to non-thinking turns. That form shows up |
| <strong>0 times in 1,000 training turns</strong> |
| of this corpus — a no-thoughts turn simply |
| carries no channel — so the template here drops |
| it. The stock template ships alongside as |
| <code>chat_template.gemma-it-original.jinja</code>. |
| Restore it and you push the model out of |
| distribution: reasoning leaks into the answer |
| and tool calls lose their opener. |
| </p> |
| </div> |
| <p> |
| What the thoughts look like depends on the system |
| prompt. Under a SillyTavern-style character card |
| the model writes a structured planner (~750 chars; |
| 23/23 of the cards that opened a channel). Under |
| the corpus's own RP framing it writes short |
| first-person interiority (~90 chars). The model |
| learned both forms separately, and the prompt picks |
| which one you get. |
| </p> |
| <p>The planner, when it shows up:</p> |
| <pre class="code-block"> |
| SCENE: where/when, atmosphere, key environmental details currently in play |
| CHARACTERS: who is present and their current physical/emotional state and motivation |
| CONTINUITY: established facts that must stay consistent |
| THREADS: active tensions and where they stand right now |
| PLAN: what THIS turn needs to accomplish and the approach it takes |
| </pre> |
| <p> |
| One more thing to expect: a conversational |
| companion persona usually produces no thought |
| channel at all (0/6 in testing), even with thinking |
| on. Companion rows in the corpus are mostly |
| non-thinking, and the model follows the data. |
| </p> |
| <h3>Tool calling</h3> |
| <p> |
| Gemma 4 tool calls use a DSL, <strong>not |
| JSON</strong>: |
| </p> |
| <pre class="code-block"> |
| FORM: <|tool_call>call:NAME{key:<|"|>value<|"|>}<tool_call|> |
| EXAMPLE: <|tool_call>call:get_weather{city:<|"|>Lisbon<|"|>}<tool_call|> |
| </pre> |
| <div class="notice"> |
| <h3>Serve tool calls inside one turn</h3> |
| <p> |
| In the training corpus a whole tool episode |
| lives inside a single |
| <code><|turn>model</code>, with |
| <code><|tool_response></code> blocks |
| interleaved inline. The model never emitted |
| <code><turn|></code> after a call, so it |
| never learned to yield there. A harness that |
| waits for <code><turn|></code> will hang |
| while the model keeps generating plausible |
| calls — the classic infinite tool loop. |
| </p> |
| <pre class="code-block"> |
| SERVE WITH: stop=["<tool_call|>"] |
| THEN: inject <|tool_response>response:NAME{...}<tool_response|> |
| and continue the SAME turn |
| NEVER: wait for <turn|> after a tool call |
| </pre> |
| </div> |
| <h3>Key Details</h3> |
| <pre class="code-block"> |
| BASE MODEL: google/gemma-4-12B |
| LICENSE: gemma |
| NOTE: the base is multimodal, so the checkpoint loads with |
| AutoModelForImageTextToText (see Quickstart)</pre> |
| <h3>Training</h3> |
| <pre class="code-block"> |
| METHOD: FULL-PARAMETER SFT -- ms-swift (swift sft), DeepSpeed ZeRO-2, |
| torch SDPA attention, custom liger fused CE |
| STAGES: three, each tagged in this repo; main = stage 3 |
| |
| stage 1 (v1-baseline-rp) aviary burn corpus, 1 epoch |
| 1,917 steps @ lr 1e-5 eval 1.311 tok-acc 0.6465 |
| stage 2 (v2-corrected-rp) thinking-weighted resample |
| 568 steps @ lr 2e-6 eval 1.3067 tok-acc 0.6479 |
| stage 3 (main) + 4,000 converted RP-reasoning rows |
| 574 steps @ lr 2e-6 eval 1.301 tok-acc 0.6491 |
| </pre> |
| <div class="notice"> |
| <h3>Why there is a stage 3</h3> |
| <p> |
| Stage 2 could think, but only under one prompt |
| shape: 19,605 of the corpus's 20,666 |
| thought-bearing rows share a single RP framing. |
| So the model opened a thought channel on 8/8 |
| in-corpus rows — and on 1 of 25 real character |
| cards. Stage 3 mixed in RP-reasoning rows under |
| ~4,000 distinct character cards so that |
| thinking no longer depends on one specific |
| prompt. |
| </p> |
| <pre class="code-block"> |
| opens a thought channel on 25 held-out character cards |
| (846-5,053 chars, short opening message): |
| stage 2: 1/25 (4%) |
| stage 3: 23/25 (92%) |
| |
| unchanged across the pass: |
| stop rate 10/10 in both thinking and non-thinking modes |
| tool-call round trip passes |
| stray channels with thinking off: 0/3 |
| P(<channel|>) at the true close: 1.000 |
| </pre> |
| </div> |
| <h3>Sampling</h3> |
| <p> |
| Use the defaults in <code>generation_config.json</code>. |
| <pre class="code-block"> |
| "temperature": 1.0, |
| "top_k": 64, |
| "top_p": 0.95, |
| </pre> |
| </p> |
| <h3>Quickstart</h3> |
| <pre class="code-block"> |
| from transformers import AutoModelForImageTextToText, AutoTokenizer |
| tok = AutoTokenizer.from_pretrained("aimeri/spoomplesmaxx-whiskeyjack-12B") |
| model = AutoModelForImageTextToText.from_pretrained( |
| "aimeri/spoomplesmaxx-whiskeyjack-12B", |
| dtype="bfloat16", device_map="auto") |
| msgs = [{"role": "user", "content": "Solve (x + 2)^2 = 0."}] |
| ids = tok.apply_chat_template(msgs, add_generation_prompt=True, |
| enable_thinking=True, return_tensors="pt").to(model.device) |
| out = model.generate(ids, max_new_tokens=512) |
| print(tok.decode(out[0][ids.shape[1]:], skip_special_tokens=False)) |
| </pre> |
| <p>This one will hear how unhinged you are</p> |
| </div> |
| </div> |
| </div> |
| </div> |
| </div> |
| |
| </html> |
