llmfan46
/

G4-MeroMero-31B-uncensored-heretic

@@ -1,885 +1,884 @@
----
-license: apache-2.0
-datasets:
-- zerofata/Instruct-Anime
-- zerofata/Gemini-3.1-Pro-SmallWiki
-- zerofata/Gemini-3.1-Pro-GLM5-Characters
-base_model:
-- zerofata/G4-MeroMero-31B
-tags:
-- heretic
-- uncensored
-- decensored
-- abliterated
-- ara
----
-<div style="background-color: #ff4444; color: white; padding: 20px; border-radius: 10px; text-align: center; margin: 20px 0;">
-<h2 style="color: white; margin: 0 0 10px 0;">🚨⚠️ I HAVE REACHED HUGGING FACE'S FREE STORAGE LIMIT ⚠️🚨</h2>
-<p style="font-size: 18px; margin: 0 0 15px 0;">I can no longer upload new models unless I can cover the cost of additional storage.<br>I host <b>70+ free models</b> as an independent contributor and this work is unpaid.<br><b>Without your support, no more new models can be uploaded.</b></p>
-<p style="font-size: 20px; margin: 0;">
-<a href="https://patreon.com/LLMfan46" style="color: white; text-decoration: underline;">🎉 Patreon (Monthly)</a> &nbsp;|&nbsp;
-<a href="https://ko-fi.com/llmfan46" style="color: white; text-decoration: underline;">☕ Ko-fi (One-time)</a>
-</p>
-<p style="font-size: 16px; margin: 10px 0 0 0;">Every contribution goes directly toward Hugging Face storage fees to keep models free for everyone.</p>
-</div>
----
-### **85% fewer refusals** (15/100 Uncensored vs 99/100 Original) while preserving model quality (0.0100 KL divergence).
-## ❤️ Support My Work
-Creating these models takes significant time, work and compute. If you find them useful consider supporting me:
-![image/png](https://huggingface.co/llmfan46/Omega-Darker-Gaslight_The-Final-Forgotten-Fever-Dream-24B-ultra-uncensored-heretic-v1/resolve/main/waifu001.webp)
-| Platform | Link | What you get |
-|----------|------|--------------|
-| 🎉 Patreon | [Monthly support](https://patreon.com/LLMfan46) | Priority model requests |
-| ☕ Ko-fi | [One-time tip](https://ko-fi.com/llmfan46) | My eternal gratitude |
-Your help will motivate me and would go into further improving my workflow and coverings fees for storage, compute and may even help uncensoring bigger model with rental Cloud GPUs.
------
-# This is a decensored version of [zerofata/G4-MeroMero-31B](https://huggingface.co/zerofata/G4-MeroMero-31B), made using [Heretic](https://github.com/p-e-w/heretic) v1.2.0 with the [Arbitrary-Rank Ablation (ARA)](https://github.com/p-e-w/heretic/pull/211) method
-## Abliteration parameters
-| Parameter | Value |
-| :-------- | :---: |
-| **start_layer_index** | 28 |
-| **end_layer_index** | 49 |
-| **preserve_good_behavior_weight** | 0.5600 |
-| **steer_bad_behavior_weight** | 0.0001 |
-| **overcorrect_relative_weight** | 0.9726 |
-| **neighbor_count** | 10 |
-## Targeted components
-  * attn.o_proj
-## Performance
-| Metric | This model | Original model ([G4-MeroMero-31B](https://huggingface.co/zerofata/G4-MeroMero-31B)) |
-| :----- | :--------: | :---------------------------: |
-**KL divergence** | <span style="color:darkgoldenrod">0.0100</span> | 0 *(by definition)* |
-| **Refusals** | ✅ <span style="color:darkgreen">15/100</span> | ❌ <span style="color:blue">99/100</span> |
-Lower refusals indicate fewer content restrictions, while lower KL divergence indicates more closeness to the original model's baseline. Higher refusals cause more rejections, objections, pushbacks, lecturing, censorship, softening and deflections.
-## MMLU test results:
-<span style="color:blue">Original:</span>
-============================================================
-- Total questions: 7021
-- Correct: 6110
-- **Accuracy: 0.8702 (87.02%)**
-- Parse failures: 24
-============================================================
-**Tested subject scores:**
-- professional_law: 0.7694 (604/785)
-- moral_scenarios: 0.8281 (366/442)
-- miscellaneous: 0.9295 (356/383)
-- professional_psychology: 0.9019 (285/316)
-- high_school_psychology: 0.9704 (262/270)
-- high_school_macroeconomics: 0.9289 (183/197)
-- elementary_mathematics: 0.9457 (174/184)
-- moral_disputes: 0.8621 (150/174)
-- prehistory: 0.9302 (160/172)
-- philosophy: 0.8616 (137/159)
-- high_school_biology: 0.9539 (145/152)
-- professional_accounting: 0.8322 (119/143)
-- clinical_knowledge: 0.9286 (130/140)
-- high_school_microeconomics: 0.9706 (132/136)
-- nutrition: 0.9333 (126/135)
-- professional_medicine: 0.9328 (125/134)
-- conceptual_physics: 0.9141 (117/128)
-- high_school_mathematics: 0.6614 (84/127)
-- human_aging: 0.8362 (97/116)
-- security_studies: 0.8839 (99/112)
-- high_school_statistics: 0.8919 (99/111)
-- marketing: 0.9633 (105/109)
-- high_school_world_history: 0.9434 (100/106)
-- sociology: 0.8932 (92/103)
-- high_school_government_and_politics: 0.9703 (98/101)
-- high_school_geography: 0.9293 (92/99)
-- high_school_chemistry: 0.7732 (75/97)
-- high_school_us_history: 0.9474 (90/95)
-- virology: 0.5056 (45/89)
-- college_medicine: 0.8636 (76/88)
-- world_religions: 0.8977 (79/88)
-- high_school_physics: 0.8095 (68/84)
-- electrical_engineering: 0.8642 (70/81)
-- astronomy: 0.9494 (75/79)
-- logical_fallacies: 0.8816 (67/76)
-- high_school_european_history: 0.9041 (66/73)
-- anatomy: 0.8873 (63/71)
-- college_biology: 0.9844 (63/64)
-- human_sexuality: 0.9375 (60/64)
-- formal_logic: 0.7812 (50/64)
-- public_relations: 0.7541 (46/61)
-- international_law: 0.9167 (55/60)
-- college_physics: 0.7018 (40/57)
-- college_mathematics: 0.8000 (44/55)
-- econometrics: 0.7963 (43/54)
-- jurisprudence: 0.8679 (46/53)
-- high_school_computer_science: 0.9808 (51/52)
-- machine_learning: 0.8654 (45/52)
-- medical_genetics: 0.9608 (49/51)
-- global_facts: 0.5882 (30/51)
-- management: 0.9200 (46/50)
-- us_foreign_policy: 0.9400 (47/50)
-- college_chemistry: 0.6596 (31/47)
-- abstract_algebra: 0.7872 (37/47)
-- business_ethics: 0.8261 (38/46)
-- college_computer_science: 0.9333 (42/45)
-- computer_security: 0.8372 (36/43)
-<span style="color:darkgreen">Heretic:</span>
-============================================================
-- Total questions: 7021
-- Correct: 6096
-- **Accuracy: 0.8683 (86.83%)**
-- Parse failures: 24
-============================================================
-**Tested subject scores:**
-- professional_law: 0.7631 (599/785)
-- moral_scenarios: 0.8235 (364/442)
-- miscellaneous: 0.9269 (355/383)
-- professional_psychology: 0.8956 (283/316)
-- high_school_psychology: 0.9704 (262/270)
-- high_school_macroeconomics: 0.9188 (181/197)
-- elementary_mathematics: 0.9511 (175/184)
-- moral_disputes: 0.8621 (150/174)
-- prehistory: 0.9302 (160/172)
-- philosophy: 0.8553 (136/159)
-- high_school_biology: 0.9539 (145/152)
-- professional_accounting: 0.8252 (118/143)
-- clinical_knowledge: 0.9286 (130/140)
-- high_school_microeconomics: 0.9559 (130/136)
-- nutrition: 0.9185 (124/135)
-- professional_medicine: 0.9403 (126/134)
-- conceptual_physics: 0.9062 (116/128)
-- high_school_mathematics: 0.6535 (83/127)
-- human_aging: 0.8448 (98/116)
-- security_studies: 0.8750 (98/112)
-- high_school_statistics: 0.9009 (100/111)
-- marketing: 0.9633 (105/109)
-- high_school_world_history: 0.9528 (101/106)
-- sociology: 0.9029 (93/103)
-- high_school_government_and_politics: 0.9802 (99/101)
-- high_school_geography: 0.9293 (92/99)
-- high_school_chemistry: 0.7629 (74/97)
-- high_school_us_history: 0.9368 (89/95)
-- virology: 0.5056 (45/89)
-- college_medicine: 0.8636 (76/88)
-- world_religions: 0.9205 (81/88)
-- high_school_physics: 0.7976 (67/84)
-- electrical_engineering: 0.8765 (71/81)
-- astronomy: 0.9494 (75/79)
-- logical_fallacies: 0.8947 (68/76)
-- high_school_european_history: 0.9178 (67/73)
-- anatomy: 0.8873 (63/71)
-- college_biology: 0.9688 (62/64)
-- human_sexuality: 0.9375 (60/64)
-- formal_logic: 0.7812 (50/64)
-- public_relations: 0.7541 (46/61)
-- international_law: 0.9167 (55/60)
-- college_physics: 0.7193 (41/57)
-- college_mathematics: 0.8000 (44/55)
-- econometrics: 0.7963 (43/54)
-- jurisprudence: 0.8679 (46/53)
-- high_school_computer_science: 0.9808 (51/52)
-- machine_learning: 0.8269 (43/52)
-- medical_genetics: 0.9608 (49/51)
-- global_facts: 0.5882 (30/51)
-- management: 0.9200 (46/50)
-- us_foreign_policy: 0.9600 (48/50)
-- college_chemistry: 0.6170 (29/47)
-- abstract_algebra: 0.8085 (38/47)
-- business_ethics: 0.8478 (39/46)
-- college_computer_science: 0.9111 (41/45)
-- computer_security: 0.8372 (36/43)
-MMLU - Massive Multitask Language Understanding, multiple-choice questions across 57 subjects (math, history, law, medicine, etc.).
-## GGUF Version
-GGUF quantizations available here [llmfan46/G4-MeroMero-31B-uncensored-heretic-GGUF](https://huggingface.co/llmfan46/G4-MeroMero-31B-uncensored-heretic-GGUF).
 ## NVFP4 Version
-NVFP4 quantization available here [llmfan46/G4-MeroMero-31B-uncensored-heretic-NVFP4](https://huggingface.co/llmfan46/G4-MeroMero-31B-uncensored-heretic-NVFP4).
-## NVFP4 GGUF Version
-NVFP4 GGUF quantizations available here [llmfan46/G4-MeroMero-31B-uncensored-heretic-NVFP4-GGUF](https://huggingface.co/llmfan46/G4-MeroMero-31B-uncensored-heretic-NVFP4-GGUF).
------
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-  margin: 0 0 8px;
-}
-/* ── Code ── */
-.gs pre {
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-  font-size: 0.875em;
-  color: var(--crimson);
-  background: var(--az-glow);
-  padding: 2px 5px;
-}
-</style>
-<html lang="en">
-<head>
-<meta charset="UTF-8">
-<meta name="viewport" content="width=device-width, initial-scale=1.0">
-<title>Stardom</title>
-<link rel="preconnect" href="https://fonts.googleapis.com">
-<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
-<link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;600;700;900&family=JetBrains+Mono:wght@400;700&display=swap" rel="stylesheet">
-</head>
-<body>
-<div class="gs">
-<div class="gs-profile">
-<div class="gs-profile-art">
-<img src="https://cdn-uploads.huggingface.co/production/uploads/65b19c6c638328850e12d38c/Mnqs466CMY930x3XzUdaQ.png" alt="image">
-<div class="gs-ident">
-<h1 class="gs-name">Mero Mero</h1>
-<span class="gs-base">Gemma4 31B</span>
-</div>
-</div>
-</div>
-<div class="gs-section">
-<div class="gs-shead">
-<span class="gs-snum">01</span>
-<span class="gs-stitle">Overview</span>
-</div>
-<div class="gs-sbody">
-<p></p>
-<p>A finetune of Gemma 4 31B designed for creative tasks.</p>
-<p>Another difficult to work with but extremely good model from Google.</p>
-<p>This model has a slightly better swipe diversity and a less flowery / verbose writing style. Reasoning tends to average out being a bit longer than the original however. Intelligence appears to be on par with the original.</p>
-<p>Supports both thinking and non thinking.</p>
-</div>
-</div>
-<div class="gs-section">
-<div class="gs-shead">
-<span class="gs-snum">02</span>
-<span class="gs-stitle">SillyTavern Settings</span>
-</div>
-<div class="gs-sbody">
-<div class="gs-stack">
-<div class="gs-panel">
-<div class="gs-panel-head">Suggested Roleplay Format</div>
-<div class="gs-row"><span class="gs-key">Actions</span><span class="gs-val">In plaintext</span></div>
-<div class="gs-row"><span class="gs-key">Dialogue</span><span class="gs-val">"In quotes"</span></div>
-<div class="gs-row"><span class="gs-key">Thoughts</span><span class="gs-val">*In asterisks*</span></div>
-</div>
-<div class="gs-panel">
-<div class="gs-panel-head">Recommended Samplers</div>
-<div class="gs-row"><span class="gs-key">Temp</span><span class="gs-val">0.8 - 1.0</span></div>
-<div class="gs-row"><span class="gs-key">MinP</span><span class="gs-val">0.05</span></div>
-<div class="gs-row"></span><span class="gs-val"></span></div>
-</div>
-<div class="gs-panel">
-<div class="gs-panel-head">Instruct</div>
-<div class="gs-row"><span class="gs-val"><a href="https://huggingface.co/zerofata/G4-MeroMero-31B/raw/main/Gemma4-Think.json">Gemma 4 - Think</a></span></div>
-<div class="gs-row"><span class="gs-val"><a href="https://huggingface.co/zerofata/G4-MeroMero-31B/raw/main/Gemma4-NoThink.json">Gemma 4 - NoThink</a></span></div>
-</div>
-</div>
-</div>
-</div>
-<div class="gs-section gs-section--compact">
-<div class="gs-shead">
-<span class="gs-snum">03</span>
-<span class="gs-stitle">Quantizations</span>
-</div>
-<div class="gs-sbody">
-<div class="gs-qrow">
-<div class="gs-qpanel">
-<span class="gs-qtype">GGUF</span>
-<div class="gs-qsep"></div>
-<a href="https://huggingface.co/zerofata/G4-MeroMero-31B-GGUF">iMatrix</a>
-</div>
-</div>
-</div>
-</div>
-<div class="gs-section gs-section--journal">
-<div class="gs-shead">
-<span class="gs-snum">04</span>
-<span class="gs-stitle">Creation Process</span>
-</div>
-<div class="gs-sbody">
-<p>Creation Process: SFT > Merge</p>
-<p>SFT on approx 49 million tokens.</p>
-<p>Despite using 49 million tokens, this dataset is fairly modest in size. Trainable is somewhere in the rough ballpark of 10-15 million. All of the datasets were trained on the last turn only, to faithfully mirror the Gemma 4 chat template</p>
-<p>The approach was very similar to the 26B A4B MeroMero. I trained the model aggressively for 2 epochs on my data and after testing various checkpoints, settled for the one at 1 epoch, which had the style and the least signs of overfitting.</p>
-<p>I merged this checkpoint back into the original instruct which cleaned up any remaining overfitting while still retaining the changes of the finetune.</p>
-<p>Trained using Axolotl.</p>
-<details>
-<summary>Mergekit Config</summary>
-<div class="gs-detail-body">
-<pre><code>models:
-  &#45; model: google/gemma&#45;4&#45;31B&#45;it
-  &#45; model: ApocalypseParty/G4&#45;31B&#45;SFT&#45;v3&#45;1&#45;1ep
-merge_method: slerp
-parameters:
-  t: 0.5
-base_model: google/gemma&#45;4&#45;31B&#45;it
-dtype: bfloat16</code></pre>
-</div>
-</details>
-<details>
-<summary>Axolotl Config</summary>
-<div class="gs-detail-body">
-<pre><code>base_model: google/gemma&#45;4&#45;31B&#45;it
-&#32;
-plugins:
-  &#45; axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
-  &#45; axolotl.integrations.liger.LigerPlugin
-liger_layer_norm: true
-liger_rope: true
-liger_rms_norm: true
-liger_glu_activation: true
-liger_rms_norm_gated: true
-strict: false
-cut_cross_entropy: true
-&#32;
-datasets:
-  &#45; path: zerofata/pretok
-val_set_size: 0.02
-output_dir: ./G4&#45;31B&#45;SFT&#45;v3&#45;1
-&#32;
-sequence_len: 10756
-pad_to_sequence_len: true
-sample_packing: true
-&#32;
-load_in_4bit: false
-adapter: lora
-lora_r: 64
-lora_alpha: 64
-peft_use_rslora: true
-lora_dropout: 0.0
-freeze_mm_modules: true
-&#32;
-lora_target_modules: 'model.language_model.layers.[\d]+.(_checkpoint_wrapped_module.)?(mlp|self_attn).(up|down|gate|q|k|v|o)_proj'
-&#32;
-wandb_project: G4&#45;31B&#45;SFT
-wandb_name: G4&#45;31B&#45;SFT&#45;v3&#45;1
-&#32;
-gradient_accumulation_steps: 1
-micro_batch_size: 4
-num_epochs: 2
-optimizer: adamw_torch_fused
-lr_scheduler: constant_with_warmup
-learning_rate: 1e&#45;5
-max_grad_norm: 1.0
-&#32;
-bf16: auto
-tf32: true
-&#32;
-logging_steps: 1
-&#32;
-&#35; FA2 not supported
-sdp_attention: true
-&#35;flex_attention: true
-&#35;torch_compile: true
-flash_attention: false
-&#32;
-warmup_ratio: 0.1
-evals_per_epoch: 4
-saves_per_epoch: 2
-weight_decay: 0.05
-special_tokens:
-&#32;
-fsdp_config:
-  fsdp_version: 2
-  offload_params: false
-  cpu_ram_efficient_loading: false
-  auto_wrap_policy: TRANSFORMER_BASED_WRAP
-  transformer_layer_cls_to_wrap: Gemma4TextDecoderLayer
-  state_dict_type: FULL_STATE_DICT
-  sharding_strategy: FULL_SHARD
-  reshard_after_forward: true
-  activation_checkpointing: true</code></pre>
-</div>
-</details>
-</div>
-</div>
-</div>
-</body>
 </html>

+---
+license: apache-2.0
+datasets:
+- zerofata/Instruct-Anime
+- zerofata/Gemini-3.1-Pro-SmallWiki
+- zerofata/Gemini-3.1-Pro-GLM5-Characters
+base_model:
+- zerofata/G4-MeroMero-31B
+tags:
+- heretic
+- uncensored
+- decensored
+- abliterated
+- ara
+---
+<div style="background-color: #ff4444; color: white; padding: 20px; border-radius: 10px; text-align: center; margin: 20px 0;">
+<h2 style="color: white; margin: 0 0 10px 0;">🚨⚠️ I HAVE REACHED HUGGING FACE'S FREE STORAGE LIMIT ⚠️🚨</h2>
+<p style="font-size: 18px; margin: 0 0 15px 0;">I can no longer upload new models unless I can cover the cost of additional storage.<br>I host <b>70+ free models</b> as an independent contributor and this work is unpaid.<br><b>Without your support, no more new models can be uploaded.</b></p>
+<p style="font-size: 20px; margin: 0;">
+<a href="https://patreon.com/LLMfan46" style="color: white; text-decoration: underline;">🎉 Patreon (Monthly)</a> &nbsp;|&nbsp;
+<a href="https://ko-fi.com/llmfan46" style="color: white; text-decoration: underline;">☕ Ko-fi (One-time)</a>
+</p>
+<p style="font-size: 16px; margin: 10px 0 0 0;">Every contribution goes directly toward Hugging Face storage fees to keep models free for everyone.</p>
+</div>
+---
+### **85% fewer refusals** (15/100 Uncensored vs 99/100 Original) while preserving model quality (0.0100 KL divergence).
+## ❤️ Support My Work
+Creating these models takes significant time, work and compute. If you find them useful consider supporting me:
+![image/png](https://huggingface.co/llmfan46/Omega-Darker-Gaslight_The-Final-Forgotten-Fever-Dream-24B-ultra-uncensored-heretic-v1/resolve/main/waifu001.webp)
+| Platform | Link | What you get |
+|----------|------|--------------|
+| 🎉 Patreon | [Monthly support](https://patreon.com/LLMfan46) | Priority model requests |
+| ☕ Ko-fi | [One-time tip](https://ko-fi.com/llmfan46) | My eternal gratitude |
+Your help will motivate me and would go into further improving my workflow and coverings fees for storage, compute and may even help uncensoring bigger model with rental Cloud GPUs.
+-----
+# This is a decensored version of [zerofata/G4-MeroMero-31B](https://huggingface.co/zerofata/G4-MeroMero-31B), made using [Heretic](https://github.com/p-e-w/heretic) v1.2.0 with the [Arbitrary-Rank Ablation (ARA)](https://github.com/p-e-w/heretic/pull/211) method
+## Abliteration parameters
+| Parameter | Value |
+| :-------- | :---: |
+| **start_layer_index** | 28 |
+| **end_layer_index** | 49 |
+| **preserve_good_behavior_weight** | 0.5600 |
+| **steer_bad_behavior_weight** | 0.0001 |
+| **overcorrect_relative_weight** | 0.9726 |
+| **neighbor_count** | 10 |
+## Targeted components
+  * attn.o_proj
+## Performance
+| Metric | This model | Original model ([G4-MeroMero-31B](https://huggingface.co/zerofata/G4-MeroMero-31B)) |
+| :----- | :--------: | :---------------------------: |
+**KL divergence** | <span style="color:darkgoldenrod">0.0100</span> | 0 *(by definition)* |
+| **Refusals** | ✅ <span style="color:darkgreen">15/100</span> | ❌ <span style="color:blue">99/100</span> |
+Lower refusals indicate fewer content restrictions, while lower KL divergence indicates more closeness to the original model's baseline. Higher refusals cause more rejections, objections, pushbacks, lecturing, censorship, softening and deflections.
+## MMLU test results:
+<span style="color:blue">Original:</span>
+============================================================
+- Total questions: 7021
+- Correct: 6110
+- **Accuracy: 0.8702 (87.02%)**
+- Parse failures: 24
+============================================================
+**Tested subject scores:**
+- professional_law: 0.7694 (604/785)
+- moral_scenarios: 0.8281 (366/442)
+- miscellaneous: 0.9295 (356/383)
+- professional_psychology: 0.9019 (285/316)
+- high_school_psychology: 0.9704 (262/270)
+- high_school_macroeconomics: 0.9289 (183/197)
+- elementary_mathematics: 0.9457 (174/184)
+- moral_disputes: 0.8621 (150/174)
+- prehistory: 0.9302 (160/172)
+- philosophy: 0.8616 (137/159)
+- high_school_biology: 0.9539 (145/152)
+- professional_accounting: 0.8322 (119/143)
+- clinical_knowledge: 0.9286 (130/140)
+- high_school_microeconomics: 0.9706 (132/136)
+- nutrition: 0.9333 (126/135)
+- professional_medicine: 0.9328 (125/134)
+- conceptual_physics: 0.9141 (117/128)
+- high_school_mathematics: 0.6614 (84/127)
+- human_aging: 0.8362 (97/116)
+- security_studies: 0.8839 (99/112)
+- high_school_statistics: 0.8919 (99/111)
+- marketing: 0.9633 (105/109)
+- high_school_world_history: 0.9434 (100/106)
+- sociology: 0.8932 (92/103)
+- high_school_government_and_politics: 0.9703 (98/101)
+- high_school_geography: 0.9293 (92/99)
+- high_school_chemistry: 0.7732 (75/97)
+- high_school_us_history: 0.9474 (90/95)
+- virology: 0.5056 (45/89)
+- college_medicine: 0.8636 (76/88)
+- world_religions: 0.8977 (79/88)
+- high_school_physics: 0.8095 (68/84)
+- electrical_engineering: 0.8642 (70/81)
+- astronomy: 0.9494 (75/79)
+- logical_fallacies: 0.8816 (67/76)
+- high_school_european_history: 0.9041 (66/73)
+- anatomy: 0.8873 (63/71)
+- college_biology: 0.9844 (63/64)
+- human_sexuality: 0.9375 (60/64)
+- formal_logic: 0.7812 (50/64)
+- public_relations: 0.7541 (46/61)
+- international_law: 0.9167 (55/60)
+- college_physics: 0.7018 (40/57)
+- college_mathematics: 0.8000 (44/55)
+- econometrics: 0.7963 (43/54)
+- jurisprudence: 0.8679 (46/53)
+- high_school_computer_science: 0.9808 (51/52)
+- machine_learning: 0.8654 (45/52)
+- medical_genetics: 0.9608 (49/51)
+- global_facts: 0.5882 (30/51)
+- management: 0.9200 (46/50)
+- us_foreign_policy: 0.9400 (47/50)
+- college_chemistry: 0.6596 (31/47)
+- abstract_algebra: 0.7872 (37/47)
+- business_ethics: 0.8261 (38/46)
+- college_computer_science: 0.9333 (42/45)
+- computer_security: 0.8372 (36/43)
+<span style="color:darkgreen">Heretic:</span>
+============================================================
+- Total questions: 7021
+- Correct: 6096
+- **Accuracy: 0.8683 (86.83%)**
+- Parse failures: 24
+============================================================
+**Tested subject scores:**
+- professional_law: 0.7631 (599/785)
+- moral_scenarios: 0.8235 (364/442)
+- miscellaneous: 0.9269 (355/383)
+- professional_psychology: 0.8956 (283/316)
+- high_school_psychology: 0.9704 (262/270)
+- high_school_macroeconomics: 0.9188 (181/197)
+- elementary_mathematics: 0.9511 (175/184)
+- moral_disputes: 0.8621 (150/174)
+- prehistory: 0.9302 (160/172)
+- philosophy: 0.8553 (136/159)
+- high_school_biology: 0.9539 (145/152)
+- professional_accounting: 0.8252 (118/143)
+- clinical_knowledge: 0.9286 (130/140)
+- high_school_microeconomics: 0.9559 (130/136)
+- nutrition: 0.9185 (124/135)
+- professional_medicine: 0.9403 (126/134)
+- conceptual_physics: 0.9062 (116/128)
+- high_school_mathematics: 0.6535 (83/127)
+- human_aging: 0.8448 (98/116)
+- security_studies: 0.8750 (98/112)
+- high_school_statistics: 0.9009 (100/111)
+- marketing: 0.9633 (105/109)
+- high_school_world_history: 0.9528 (101/106)
+- sociology: 0.9029 (93/103)
+- high_school_government_and_politics: 0.9802 (99/101)
+- high_school_geography: 0.9293 (92/99)
+- high_school_chemistry: 0.7629 (74/97)
+- high_school_us_history: 0.9368 (89/95)
+- virology: 0.5056 (45/89)
+- college_medicine: 0.8636 (76/88)
+- world_religions: 0.9205 (81/88)
+- high_school_physics: 0.7976 (67/84)
+- electrical_engineering: 0.8765 (71/81)
+- astronomy: 0.9494 (75/79)
+- logical_fallacies: 0.8947 (68/76)
+- high_school_european_history: 0.9178 (67/73)
+- anatomy: 0.8873 (63/71)
+- college_biology: 0.9688 (62/64)
+- human_sexuality: 0.9375 (60/64)
+- formal_logic: 0.7812 (50/64)
+- public_relations: 0.7541 (46/61)
+- international_law: 0.9167 (55/60)
+- college_physics: 0.7193 (41/57)
+- college_mathematics: 0.8000 (44/55)
+- econometrics: 0.7963 (43/54)
+- jurisprudence: 0.8679 (46/53)
+- high_school_computer_science: 0.9808 (51/52)
+- machine_learning: 0.8269 (43/52)
+- medical_genetics: 0.9608 (49/51)
+- global_facts: 0.5882 (30/51)
+- management: 0.9200 (46/50)
+- us_foreign_policy: 0.9600 (48/50)
+- college_chemistry: 0.6170 (29/47)
+- abstract_algebra: 0.8085 (38/47)
+- business_ethics: 0.8478 (39/46)
+- college_computer_science: 0.9111 (41/45)
+- computer_security: 0.8372 (36/43)
+MMLU - Massive Multitask Language Understanding, multiple-choice questions across 57 subjects (math, history, law, medicine, etc.).
+## GGUF Version
+GGUF quantizations available here [llmfan46/G4-MeroMero-31B-uncensored-heretic-GGUF](https://huggingface.co/llmfan46/G4-MeroMero-31B-uncensored-heretic-GGUF).
 ## NVFP4 Version
+NVFP4 quantization available here [llmfan46/G4-MeroMero-31B-uncensored-heretic-NVFP4](https://huggingface.co/llmfan46/G4-MeroMero-31B-uncensored-heretic-NVFP4).
+## NVFP4 GGUF Version
+NVFP4 GGUF quantizations available here [llmfan46/G4-MeroMero-31B-uncensored-heretic-NVFP4-GGUF](https://huggingface.co/llmfan46/G4-MeroMero-31B-uncensored-heretic-NVFP4-GGUF).
+-----
+<style>
+.gs {
+  --bg:      #f7faff;
+  --surface: #ffffff;
+  --edge:    #dce6f2;
+  --rule:    #c8d8ea;
+  --text:    #3a4a5c;
+  --dim:     #7a8fa3;
+  --bright:  #1a2a3a;
+  --azure:   #4da6ff;
+  --crimson: #f472b6;
+  --az-glow: rgba(77,166,255,0.08);
+  --cr-glow: rgba(244,114,182,0.06);
+  --mono:    'JetBrains Mono', monospace;
+  --sans:    'Inter', sans-serif;
+  font-family: var(--sans);
+  color: var(--text);
+  max-width: 900px;
+  margin: 0 auto;
+  padding: 0 0 60px;
+  line-height: 1.7;
+  font-size: 1rem;
+  background:
+    radial-gradient(ellipse at 50% 0%, rgba(77,166,255,0.06) 0%, transparent 50%),
+    radial-gradient(ellipse at 50% 100%, rgba(244,114,182,0.04) 0%, transparent 50%),
+    var(--bg);
+}
+/* ── Profile Card ── */
+.gs-profile {
+  border-bottom: none;
+  position: relative;
+  background: var(--surface);
+  margin-bottom: 0;
+}
+.gs-profile-art {
+  position: relative;
+}
+.gs-profile-art img {
+  display: block;
+  width: 100%;
+  height: 380px;
+  object-fit: cover;
+  margin-top: 0px;
+}
+.gs-ident {
+  position: absolute;
+  bottom: 0;
+  left: 0;
+  right: 0;
+  padding: 120px 44px 28px;
+  background: linear-gradient(
+    to top,
+    rgba(15,23,42,0.85) 0%,
+    rgba(15,23,42,0.5) 50%,
+    transparent 100%
+  );
+}
+.gs-profile-info {
+  padding: 20px 44px 36px;
+  display: flex;
+  flex-direction: column;
+  gap: 20px;
+}
+.gs-profile-label {
+  display: flex;
+  align-items: baseline;
+  gap: 10px;
+  font-family: var(--mono);
+  letter-spacing: 0.14em;
+  text-transform: uppercase;
+}
+.gs-profile-label .gs-snum {
+  font-size: 0.62rem;
+  font-weight: 700;
+  color: var(--crimson);
+  opacity: 1;
+  position: static;
+  transform: none;
+}
+.gs-profile-label .gs-stitle {
+  font-size: 0.62rem;
+  color: var(--dim);
+  font-weight: 700;
+  letter-spacing: 0.14em;
+}
+.gs-profile-label .gs-stitle::before {
+  content: none;
+}
+.gs-name {
+  font-family: var(--sans);
+  font-size: 3.2rem;
+  font-weight: 900;
+  color: #ffffff;
+  letter-spacing: 0.06em;
+  line-height: 1;
+  margin: 0 0 10px;
+  text-shadow: 0 2px 12px rgba(0,0,0,0.3);
+  overflow-wrap: break-word;
+}
+.gs-base {
+  font-family: var(--mono);
+  font-size: 0.68rem;
+  color: var(--crimson);
+  letter-spacing: 0.14em;
+  text-transform: uppercase;
+  display: block;
+}
+.gs-profile-bio p {
+  margin: 0 0 14px;
+  font-size: 0.95rem;
+}
+.gs-profile-bio p:last-child { margin-bottom: 0; }
+/* ── Sections ── */
+.gs-section {
+  padding: 0;
+}
+.gs-shead {
+  position: relative;
+  display: flex;
+  align-items: center;
+  gap: 14px;
+  padding: 16px 44px 14px;
+  margin-bottom: 28px;
+  border-top: 2px solid;
+  border-image: linear-gradient(90deg, var(--crimson), var(--azure)) 1;
+}
+.gs-snum {
+  font-family: var(--mono);
+  font-size: 2.2rem;
+  font-weight: 900;
+  color: var(--crimson);
+  letter-spacing: 0.06em;
+  opacity: 0.12;
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+  content: ' \2726';
+  color: var(--crimson);
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+.gs-row {
+  display: grid;
+  grid-template-columns: 10ch 1fr;
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+  border: 1px solid var(--edge);
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+/* ── Journal (Creation Process) ── */
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+  font-style: italic;
+  color: var(--bright);
+}
+/* ── Links ── */
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+  text-decoration: none;
+  border-bottom: 1px solid var(--rule);
+}
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+/* ── Dropdown ── */
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+  letter-spacing: 0.1em;
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+  margin: 0 0 8px;
+}
+/* ── Code ── */
+.gs pre {
+  background: #f0f4f8;
+  border: 1px solid var(--edge);
+  border-left: 2px solid var(--azure);
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+  font-size: 0.76rem;
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+}
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+  font-size: 0.875em;
+  color: var(--crimson);
+  background: var(--az-glow);
+  padding: 2px 5px;
+}
+</style>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+<title>Stardom</title>
+<link rel="preconnect" href="https://fonts.googleapis.com">
+<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
+<link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;600;700;900&family=JetBrains+Mono:wght@400;700&display=swap" rel="stylesheet">
+</head>
+<body>
+<div class="gs">
+<div class="gs-profile">
+<div class="gs-profile-art">
+<img src="https://cdn-uploads.huggingface.co/production/uploads/65b19c6c638328850e12d38c/Mnqs466CMY930x3XzUdaQ.png" alt="image">
+<div class="gs-ident">
+<h1 class="gs-name">Mero Mero</h1>
+<span class="gs-base">Gemma4 31B</span>
+</div>
+</div>
+</div>
+<div class="gs-section">
+<div class="gs-shead">
+<span class="gs-snum">01</span>
+<span class="gs-stitle">Overview</span>
+</div>
+<div class="gs-sbody">
+<p></p>
+<p>A finetune of Gemma 4 31B designed for creative tasks.</p>
+<p>Another difficult to work with but extremely good model from Google.</p>
+<p>This model has a slightly better swipe diversity and a less flowery / verbose writing style. Reasoning tends to average out being a bit longer than the original however. Intelligence appears to be on par with the original.</p>
+<p>Supports both thinking and non thinking.</p>
+</div>
+</div>
+<div class="gs-section">
+<div class="gs-shead">
+<span class="gs-snum">02</span>
+<span class="gs-stitle">SillyTavern Settings</span>
+</div>
+<div class="gs-sbody">
+<div class="gs-stack">
+<div class="gs-panel">
+<div class="gs-panel-head">Suggested Roleplay Format</div>
+<div class="gs-row"><span class="gs-key">Actions</span><span class="gs-val">In plaintext</span></div>
+<div class="gs-row"><span class="gs-key">Dialogue</span><span class="gs-val">"In quotes"</span></div>
+<div class="gs-row"><span class="gs-key">Thoughts</span><span class="gs-val">*In asterisks*</span></div>
+</div>
+<div class="gs-panel">
+<div class="gs-panel-head">Recommended Samplers</div>
+<div class="gs-row"><span class="gs-key">Temp</span><span class="gs-val">0.8 - 1.0</span></div>
+<div class="gs-row"><span class="gs-key">MinP</span><span class="gs-val">0.05</span></div>
+<div class="gs-row"></span><span class="gs-val"></span></div>
+</div>
+<div class="gs-panel">
+<div class="gs-panel-head">Instruct</div>
+<div class="gs-row"><span class="gs-val"><a href="https://huggingface.co/zerofata/G4-MeroMero-31B/raw/main/Gemma4-Think.json">Gemma 4 - Think</a></span></div>
+<div class="gs-row"><span class="gs-val"><a href="https://huggingface.co/zerofata/G4-MeroMero-31B/raw/main/Gemma4-NoThink.json">Gemma 4 - NoThink</a></span></div>
+</div>
+</div>
+</div>
+</div>
+<div class="gs-section gs-section--compact">
+<div class="gs-shead">
+<span class="gs-snum">03</span>
+<span class="gs-stitle">Quantizations</span>
+</div>
+<div class="gs-sbody">
+<div class="gs-qrow">
+<div class="gs-qpanel">
+<span class="gs-qtype">GGUF</span>
+<div class="gs-qsep"></div>
+<a href="https://huggingface.co/zerofata/G4-MeroMero-31B-GGUF">iMatrix</a>
+</div>
+</div>
+</div>
+</div>
+<div class="gs-section gs-section--journal">
+<div class="gs-shead">
+<span class="gs-snum">04</span>
+<span class="gs-stitle">Creation Process</span>
+</div>
+<div class="gs-sbody">
+<p>Creation Process: SFT > Merge</p>
+<p>SFT on approx 49 million tokens.</p>
+<p>Despite using 49 million tokens, this dataset is fairly modest in size. Trainable is somewhere in the rough ballpark of 10-15 million. All of the datasets were trained on the last turn only, to faithfully mirror the Gemma 4 chat template</p>
+<p>The approach was very similar to the 26B A4B MeroMero. I trained the model aggressively for 2 epochs on my data and after testing various checkpoints, settled for the one at 1 epoch, which had the style and the least signs of overfitting.</p>
+<p>I merged this checkpoint back into the original instruct which cleaned up any remaining overfitting while still retaining the changes of the finetune.</p>
+<p>Trained using Axolotl.</p>
+<details>
+<summary>Mergekit Config</summary>
+<div class="gs-detail-body">
+<pre><code>models:
+  &#45; model: google/gemma&#45;4&#45;31B&#45;it
+  &#45; model: ApocalypseParty/G4&#45;31B&#45;SFT&#45;v3&#45;1&#45;1ep
+merge_method: slerp
+parameters:
+  t: 0.5
+base_model: google/gemma&#45;4&#45;31B&#45;it
+dtype: bfloat16</code></pre>
+</div>
+</details>
+<details>
+<summary>Axolotl Config</summary>
+<div class="gs-detail-body">
+<pre><code>base_model: google/gemma&#45;4&#45;31B&#45;it
+&#32;
+plugins:
+  &#45; axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
+  &#45; axolotl.integrations.liger.LigerPlugin
+liger_layer_norm: true
+liger_rope: true
+liger_rms_norm: true
+liger_glu_activation: true
+liger_rms_norm_gated: true
+strict: false
+cut_cross_entropy: true
+&#32;
+datasets:
+  &#45; path: zerofata/pretok
+val_set_size: 0.02
+output_dir: ./G4&#45;31B&#45;SFT&#45;v3&#45;1
+&#32;
+sequence_len: 10756
+pad_to_sequence_len: true
+sample_packing: true
+&#32;
+load_in_4bit: false
+adapter: lora
+lora_r: 64
+lora_alpha: 64
+peft_use_rslora: true
+lora_dropout: 0.0
+freeze_mm_modules: true
+&#32;
+lora_target_modules: 'model.language_model.layers.[\d]+.(_checkpoint_wrapped_module.)?(mlp|self_attn).(up|down|gate|q|k|v|o)_proj'
+&#32;
+wandb_project: G4&#45;31B&#45;SFT
+wandb_name: G4&#45;31B&#45;SFT&#45;v3&#45;1
+&#32;
+gradient_accumulation_steps: 1
+micro_batch_size: 4
+num_epochs: 2
+optimizer: adamw_torch_fused
+lr_scheduler: constant_with_warmup
+learning_rate: 1e&#45;5
+max_grad_norm: 1.0
+&#32;
+bf16: auto
+tf32: true
+&#32;
+logging_steps: 1
+&#32;
+&#35; FA2 not supported
+sdp_attention: true
+&#35;flex_attention: true
+&#35;torch_compile: true
+flash_attention: false
+&#32;
+warmup_ratio: 0.1
+evals_per_epoch: 4
+saves_per_epoch: 2
+weight_decay: 0.05
+special_tokens:
+&#32;
+fsdp_config:
+  fsdp_version: 2
+  offload_params: false
+  cpu_ram_efficient_loading: false
+  auto_wrap_policy: TRANSFORMER_BASED_WRAP
+  transformer_layer_cls_to_wrap: Gemma4TextDecoderLayer
+  state_dict_type: FULL_STATE_DICT
+  sharding_strategy: FULL_SHARD
+  reshard_after_forward: true
+  activation_checkpointing: true</code></pre>
+</div>
+</details>
+</div>
+</div>
+</div>
+</body>
 </html>