| --- |
| license: apache-2.0 |
| base_model: ByteDance-Seed/Seed-OSS-36B-Base-woSyn |
| library_name: transformers |
| pipeline_tag: text-generation |
| tags: |
| - roleplay |
| - creative-writing |
| language: |
| - en |
| --- |
| <!doctype html> |
| <html lang="en"> |
| <head> |
| <meta charset="UTF-8" /> |
| <meta name="viewport" content="width=device-width, initial-scale=1.0" /> |
| <title>SpoomplesMaxx Mockingbird 36B</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%; |
| 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%; |
| 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-Mockingbird-36B</h2> |
| <h3>"Fat Mockingbird"</h3> |
| <pre class="code-block-image"> |
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| </pre> |
| </div> |
| <p> |
| <strong>"Many-Tongued"</strong> — <em>Mimus |
| polyglottos</em>, the many-tongued mimic. A bird |
| with no song of its own and therefore all of them: |
| it will do the cardinal, the car alarm, the creaky |
| gate, and a frog if it hears one. First of the |
| mimids, the family that follows the corvids. |
| </p> |
| <p> |
| The corvids (jackdaw, magpie, whiskeyjack) were |
| generalists with a roleplay bent. mockingbird flips |
| the recipe: <strong>a model that is 100% about |
| roleplay, trained mostly on things that are not |
| roleplay.</strong> That is not a contradiction — it |
| is the finding. Measured across the strongest open |
| RP lineage I know |
| (<a href="https://huggingface.co/PocketDoc/Dans-PersonalityEngine-V1.3.0-24b">Dans-PersonalityEngine</a>), |
| roughly 590K of its rows are |
| task/reasoning/assistant/world-knowledge data |
| against ~150K of actual roleplay. RP is the |
| product; RP is not the corpus. The RP data teaches |
| the register. Everything else teaches the mind |
| behind it. |
| </p> |
| <p> |
| Built on <strong>Seed-OSS-36B-Base-woSyn</strong> — |
| the base ByteDance trained <em>without</em> |
| synthetic instruction data. The wildest 36B |
| available: nobody else's assistant habits, nobody |
| else's turn-taking tics. A blank throat, ready to |
| mimic. |
| </p> |
| <h3>Who this is for</h3> |
| <p> |
| 36B dense is a lot of model, and no friend to the |
| VRAM-challenged — something I'm genuinely sorry |
| about. But the target here was the best-quality RP |
| under 70B, and every choice in this card spends |
| toward that target. It won't be for everyone, and |
| it doesn't have to be: whiskeyjack exists for |
| exactly that reason. The mimids are an experiment |
| in RP quality, exclusively. The 3-bit quants |
| (~18GB) are as small as this one gets. |
| </p> |
| <h3>Prompt format</h3> |
| <p> |
| Native Seed convention. No new tokens were harmed |
| in the making of this model. |
| </p> |
| <pre class="code-block"> |
| FORM <seed:bos>system\n{card}<seed:eos><seed:bos>user\n{text}<seed:eos><seed:bos>assistant\n{reply}<seed:eos> |
| STOPS <seed:eos> |
| ROLES system / user / assistant |
| |
| EXAMPLE |
| <seed:bos>system |
| You are Bram Hollis, keeper of the Wayward Lantern...<seed:eos><seed:bos>user |
| *I push the door open, dripping wet* Got room for one more?<seed:eos><seed:bos>assistant |
| </pre> |
| <p> |
| The template ships embedded |
| (<code>chat_template.jinja</code> + |
| <code>tokenizer_config.json</code>), so vLLM, |
| llama.cpp, and the quants pick it up without |
| ceremony. Anything that can serve Seed-OSS-Instruct |
| serves mockingbird. |
| </p> |
| <div class="notice"> |
| <h3>No thinking. Ever.</h3> |
| <p> |
| mockingbird never emits |
| <code><seed:think></code> and was never |
| trained on reasoning traces |
| </p> |
| </div> |
| <h3>Tool calling</h3> |
| <p> |
| The corpus includes the full Toolmaxx family |
| (58,095 conversations), rendered with tool |
| responses as a plain <code>tool</code> role turn: |
| </p> |
| <pre class="code-block"> |
| <seed:bos>tool\n{tool output}<seed:eos> |
| </pre> |
| <div class="notice"> |
| <h3>Not the Seed-OSS-Instruct tool DSL.</h3> |
| <p> |
| No <code><seed:tool_call></code> tokens, |
| no <code><function=...></code> markup. |
| Tool competence here is corpus-taught and |
| conversational, not a structured calling API. |
| If you need strict function calling, put a |
| schema in the card and validate what comes back |
| </p> |
| </div> |
| <h3>Key details</h3> |
| <pre class="code-block"> |
| BASE ByteDance-Seed/Seed-OSS-36B-Base-woSyn (Apache 2.0) |
| PARAMS 36B dense · 64 layers · GQA 8 KV heads · head_dim 128 |
| VOCAB 155,136 · native Seed control tokens · zero added tokens |
| CTX trained at 24,576 packed · base RoPE to 512K |
| CORPUS 667,332 conversations · ~1.3B supervised chars · 43% RP share |
| THINKING none, by construction |
| LANGUAGE English (non-English filtered at ingest) |
| </pre> |
| <h3>Training</h3> |
| <p> |
| Full-parameter SFT, |
| <a href="https://github.com/axolotl-ai-cloud/axolotl">Axolotl</a>, |
| 8×B200. One stage, no annealing games: |
| </p> |
| <pre class="code-block"> |
| STEPS 584 run of 910 planned (funding cliff) · this release = step 450 |
| SEQ 24,576 · sample packing (99.94% efficiency) |
| BATCH 64 global (micro 1 × accum 8 × 8 GPUs) |
| OPT AdamW · lr 8e-6 cosine · 3% warmup · wd 0.01 · bf16 |
| STACK FSDP2 full-shard · activation checkpointing · Cut Cross Entropy |
| |
| VAL PPL base 4.272 → step 100: 4.094 (min) → step 550: 4.179 |
| </pre> |
| <p> |
| Val perplexity bottoms out early and drifts up; it |
| did not pick this checkpoint. Selection ran the |
| other way: every 50th checkpoint through a seeded |
| multi-turn loop/stall battery (×5 repeats), a |
| 20-arm sampler sweep across the finalists |
| (400/450/500) at 16K context, and blind-judged |
| episodes on real character cards. Step 450 won on |
| both instruments: the highest battery pass rate in |
| the whole sweep matrix at its shipped sampler, and |
| the most coherent judged episodes. Earlier |
| checkpoints still loop; later ones need |
| temperatures where coherence frays. |
| </p> |
| <p> |
| The corpus is the PersonalityEngine V1.3.0 public |
| list — all 42 non-gated sets, ingested verbatim — |
| plus my own lanes on top: 16,714 carded RP |
| conversations (anthracite c2, Gryphe Aesir, |
| PJMixers, bluemoon), 8,872 think-stripped RP logs, |
| and a 385-conversation anti-repetition lane built |
| to reconstruct the gated RepRemover idea: find the |
| turn that repeats an earlier turn, cut there, |
| rewrite the continuation to advance the scene, |
| accept only if it clears a Jaccard 0.35 gate |
| against every prior turn. |
| </p> |
| <div class="notice"> |
| <h3>The corpus was cleaned so the model doesn't have to be.</h3> |
| <p> |
| Dropped at ingest, with receipts: |
| <code>Name:</code>-style fiction-transcript |
| openers (up to 18.2% of one source — the |
| classic RP defect), mid-scene policy refusals |
| and jailbreak-compliance preambles (851 + 452 |
| conversations - not really needed for this |
| model), non-English rows, exact duplicates |
| across lanes (5,332). Conversations longer than |
| the context window were split at turn |
| boundaries with the card re-carried, not |
| truncated (one Personamaxx-VN row was a single |
| 4.85M-char turn; it did not make the cut). |
| </p> |
| </div> |
| <h3>Sampling</h3> |
| <p> |
| The shipped <code>generation_config.json</code> is |
| the measured optimum, not a guess — it won a 20-arm |
| sweep (temperature × top_p × min_p × penalties, ×5 |
| seeded battery runs per arm, plus blind-judged |
| episodes): |
| </p> |
| <pre class="code-block"> |
| temperature 1.0 · top_p 0.9 · no penalties |
| </pre> |
| <p> |
| The usable window is narrow and hotter than RP |
| muscle memory expects: <strong>~0.95–1.05</strong>. |
| Below ~0.85 the model collapses into verbatim |
| self-repetition (at 0.7 it re-emits its previous |
| turn nearly word for word). Above ~1.15 |
| turn-endings slip and the prose goes dreamlike. |
| min_p alone (0.05, top_p off) truncates harder than |
| top_p 0.9 and loops <em>more</em>, not less. This |
| is not a temperature-0.7 model. |
| </p> |
| <div class="notice"> |
| <h3>Never use repetition, presence, or frequency penalties.</h3> |
| <p> |
| The Seed template ends every message with |
| <code><seed:eos></code>, so a multi-turn |
| chat has dozens of them in context. |
| Context-wide penalties tax that token directly: |
| the model stops being able to end its turn, the |
| penalty then strip-mines the English |
| vocabulary, and generation falls into the base |
| model's untrained Chinese tokens |
| (<code>爹爹爹爹爹…</code> — it is exactly as |
| bad as it looks). If you need anti-repetition, |
| use DRY or XTC, which leave special tokens |
| alone. The corpus's anti-repetition lane plus |
| temperature 1.0 is the intended mechanism. |
| </p> |
| </div> |
| <p> |
| Give it a proper card and it will give you a proper |
| character: the model was fed real character cards |
| (median ~3K chars, p90 ~8.5K) as system messages. |
| </p> |
| <h3>Quickstart</h3> |
| <pre class="code-block"> |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| model_id = "aimeri/spoomplesmaxx-mockingbird-36B" |
| tok = AutoTokenizer.from_pretrained(model_id) |
| model = AutoModelForCausalLM.from_pretrained( |
| model_id, torch_dtype="bfloat16", device_map="auto") |
| |
| messages = [ |
| {"role": "system", "content": "You are Bram Hollis, keeper of the " |
| "Wayward Lantern, a roadside inn on the edge of the fen. Gruff, " |
| "observant, superstitious. Third person, *asterisk action beats*."}, |
| {"role": "user", "content": "*I push the door open, dripping wet* " |
| "Got room for one more tonight?"}, |
| ] |
| ids = tok.apply_chat_template(messages, add_generation_prompt=True, |
| return_tensors="pt").to(model.device) |
| out = model.generate(ids, max_new_tokens=400, temperature=1.0, top_p=0.9, |
| do_sample=True) |
| print(tok.decode(out[0][ids.shape[-1]:], skip_special_tokens=True)) |
| </pre> |
| <p>Quants: |
| <a href="https://huggingface.co/aimeri/spoomplesmaxx-mockingbird-36B-mlx-3bit">MLX 3-bit</a> (15GB, Apple silicon) · |
| <a href="https://huggingface.co/aimeri/spoomplesmaxx-mockingbird-36B-GGUF">GGUF static Q3–Q5</a> · |
| <a href="https://huggingface.co/aimeri/spoomplesmaxx-mockingbird-36B-i1-GGUF">GGUF imatrix</a> |
| (weighted on the model’s own corpus — prefer these at 3–4 bit; |
| i1-Q3_K_M is the 18GB target, i1-IQ3_XXS squeezes to 14GB)</p> |
| <p>This one already knows your character better than you do.</p> |
| <p> |
| <em>mockingbird is a roleplay and creative-writing |
| model for adults. It stays in character by design — |
| its corpus was scrubbed of mid-scene refusals — so |
| bring your own moderation where your deployment |
| needs it. Not an assistant, not an oracle, not for |
| anything safety-critical.</em> |
| </p> |
| <p> |
| <em>mimids 01 · trained 2026-08 · checkpoints |
| published live at |
| <a href="https://huggingface.co/aimeri/mockingbird-v1-seedoss-ckpts">mockingbird-v1-seedoss-ckpts</a> |
| · Apache 2.0</em> |
| </p> |
| </div> |
| </div> |
| </div> |
| </div> |
| </div> |
| |
| </html> |
